Contemporary Endocrinology
Series Editor: Leonid Poretsky
Anthony C. Hackney
Naama W. Constantini Editors
Endocrinology
of Physical
Activity and
Sport
Third Edition
Contemporary Endocrinology
Series Editor
Leonid Poretsky
Division of Endocrinology
Lenox Hill Hospital
New York, NY, USA
More information about this series at http://www.springer.com/series/7680
Anthony C. Hackney
Naama W. Constantini
Editors
Endocrinology
of Physical Activity
and Sport
Third Edition
Editors
Anthony C. Hackney
Department of Exercise & Sport
Science, Department of Nutrition
University of North Carolina
Chapel Hill, NC
USA
Naama W. Constantini
Heidi Rothberg Sport Medicine Center
Shaare Zedek Medical Center
Jerusalem
Jerusalem
Israel
ISSN 2523-3785 ISSN 2523-3793 (electronic)
Contemporary Endocrinology
ISBN 978-3-030-33375-1 ISBN 978-3-030-33376-8 (eBook)
https://doi.org/10.1007/978-3-030-33376-8
© Springer Nature Switzerland AG 2020
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or
part of the material is concerned, specifically the rights of translation, reprinting, reuse of
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and transmission or information storage and retrieval, electronic adaptation, computer software,
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The use of general descriptive names, registered names, trademarks, service marks, etc. in this
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The publisher, the authors and the editors are safe to assume that the advice and information in
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This book is dedicated to my mentor, the late Professor Atko Viru,
and my family who have always provided unwavering support
for me. My since thanks and loving gratitude to each of you.
– Anthony C. Hackney
I dedicate this book to my late parents, Prof. RJZ Werblowsky
and his beloved wife, Aliza, who passed away since the last
edition. I owe them both my family and career.
– Naama W. Constantini
While finalizing this edition, Dr. Barbara Drinkwater, the pioneer
of female athlete sports medicine and science research, has
passed away. She will always be remembered as the first woman
president of the American College of Sports Medicine and a
leader to so many of us, especially in the field of eating disorders,
menstrual irregularities, and bone health. The chapters in this
book dealing with female physiology and endocrinology are
honorably dedicated to her.
– Naama W. Constantini and Anthony C. Hackney
v
Series Editor Foreword
With the twin epidemics of obesity and diabetes upon us, endocrinologists
often counsel patients on the benefits of exercise. During our many years of
training, however, relatively little time is spent learning about the relationship
between exercise and the endocrine system. To address this deficit, the volume edited by Drs. Anthony C. Hackney and Naama W. Constantini and written by an illustrious international group of experts provides an immense
wealth of information on the topic.
The relationship between exercise and the endocrine system is complicated and bidirectional: the effectiveness of exercise training in part depends
on the state of the endocrine system, while all components of the endocrine
system can be dramatically affected by exercise. The interactions between
hormones and exercise extend well beyond the obvious (exercise and energy
metabolism, exercise and diabetes) to include reproductive, adrenal and
growth hormone axes, as well as bone metabolism, thyroid function, endogenous opiates, and circadian endocrine physiology, among others. Moreover,
the relationship between the endocrine system and exercise evolves during
the person’s lifetime (from childhood to puberty to advanced age) and is
affected by both type and intensity of exercise (e.g., acute vs. chronic, moderate exercise vs. Olympic athlete training, etc.).
Given these complexities, it is remarkable how clearly and completely the
authors of this encyclopedic text have been able to cover their subject. The
book is a true pleasure to read. It is exceptionally well referenced and, without a doubt, will become a valuable resource for anybody interested in human
physiology. This most certainly includes endocrinologists, who, after becoming familiar with the content of this volume, will find themselves on a much
firmer ground while advising their patients on the myriads of benefits, as well
as some potential risks, of exercise.
New York, NY, USA
Leonid Poretsky, MD
vii
Preface
The first edition of this book was entitled Sports Endocrinology edited by
Michelle P. Warren and Naama W. Constantini and published in 2000. It was
the first book with incursions into this complex and critically important topic
area of exercise, sports, and hormones. It answered a recognized need and
was well received by the scientific community. Twelve years later, the book
took on a new expanded title, new editorship, and new authorship of chapter
topics, and the second edition was published. It too was highly popular and a
leading volume on the discipline. Now, after five additional years, a third edition has been developed with revised and updated content as well as new
expanded materials. Nevertheless, over its evolution and multiple editions,
the emphasis of the book has remained the same: to provide the reader with
current, insightful discussion of the key elements of endocrinology as they
relate to physical activity, exercise, and sports.
Endocrinology is a demanding scientific endeavor and when overlaid with
the unique aspects of the physical stress of exercise and exercise training can
become a daunting topic. The editors are profoundly grateful to the contributor’s authors who have painstakingly and carefully crafted each of their discussions to aid the reader in overcoming what some might consider an
insurmountable set of topics. The author’s scholarship, devotion to the scientific method, and overall professionalism have allowed for a new edition that
not only reflects the present state of knowledge on each of their topics but will
undoubtedly serve as a stimulus for further advances in this highly dynamic,
constantly evolving, and challenging subject. Our sincere thanks to each of
them for their efforts. We hope the readers will enjoy this new edition and it
spurs them to ask new research questions.
Chapel Hill, NC, USA
Jerusalem, Israel
Anthony C. Hackney, PhD, DSc
Naama W. Constantini, MD
ix
Contents
1Methodological Considerations in Exercise Endocrinology�������� 1
Anthony C. Hackney, Abbie E. Smith-Ryan,
and Julius E. Fink
2Endogenous Opiates and Exercise-­Related Hypoalgesia ������������ 19
Allan H. Goldfarb, Robert R. Kraemer,
and Brandon A. Baiamonte
3The Effect of Exercise on the Hypothalamic-PituitaryAdrenal Axis ������������������������������������������������������������������������������������ 41
David H. St-Pierre and Denis Richard
4Impact of Chronic Training on Pituitary Hormone
Secretion in Humans������������������������������������������������������������������������ 55
Johannes D. Veldhuis and Kohji Yoshida
5Exercise and the GH-IGF-I Axis���������������������������������������������������� 71
Alon Eliakim and Dan Nemet
6Exercise and Thyroid Function������������������������������������������������������ 85
Dorina Ylli, Joanna Klubo-Gwiezdzinska,
and Leonard Wartofsky
7The Male Reproductive System, Exercise,
and Training: Endocrine Adaptations�������������������������������������������� 109
Fabio Lanfranco and Marco Alessandro Minetto
8Exercise and the Hypothalamus: Ovulatory Adaptations������������ 123
Angela Y. Liu, Moira A. Petit, and Jerilynn C. Prior
9Adrenergic Regulation of Energy Metabolism������������������������������ 153
Michael Kjær and Kai Lange
10Sex Differences in Energy Balance and Weight Control�������������� 161
Kristin S. Ondrak
11Exercise Training in the Normal Female: Effects
of Low Energy Availability on Reproductive Function���������������� 171
Anne B. Loucks
12Ghrelin Responses to Acute Exercise and Training���������������������� 193
Jaak Jürimäe
xi
xii
13Hormonal Regulation of Fluid and Electrolyte
Homeostasis During Exercise���������������������������������������������������������� 209
Charles E. Wade
14Hormonal Regulation of the Positive and Negative
Effects of Exercise on Bone ������������������������������������������������������������ 229
Whitney R.D. Duff and Philip D. Chilibeck
15Interrelations Between Acute and Chronic Exercise
Stress and the Immune and Endocrine Systems �������������������������� 249
Jonathan Peake
16Effects of Female Reproductive Hormones
on Sports Performance�������������������������������������������������������������������� 267
Constance M. Lebrun, Sarah M. Joyce,
and Naama W. Constantini
17Endocrine Implications of Relative Energy
Deficiency in Sport �������������������������������������������������������������������������� 303
Katherine M. Cooper and Kathryn E. Ackerman
18Vitamin D and Exercise Performance�������������������������������������������� 321
Joi J. Thomas and D. Enette Larson-Meyer
19The Effects of Altitude on the Hormonal Response
to Physical Exercise�������������������������������������������������������������������������� 341
Nunzia Prencipe, Chiara Bona, Fabio Lanfranco,
Silvia Grottoli, and Andrea Silvio Benso
20An Introduction to Circadian Endocrine Physiology:
Implications for Exercise and Sports Performance���������������������� 363
Teodor T. Postolache, Arshpreet Gulati,
Olaoluwa O. Okusaga, and John W. Stiller
21The Role of Hormones in Exercise-­Induced
Muscle Hypertrophy������������������������������������������������������������������������ 391
Julius E. Fink
22Endocrine Responses to Acute and Chronic Exercise
in the Developing Child ������������������������������������������������������������������ 399
Daniela A. Rubin
23Exercise in Older Adults: The Effect of Age on Exercise
Endocrinology���������������������������������������������������������������������������������� 421
Jennifer L. Copeland
24Immune, Endocrine, and Soluble Factor Interactions
During Aerobic Exercise in Cancer Survivors������������������������������ 441
Elizabeth S. Evans, Erik D. Hanson, and Claudio L. Battaglini
25Type I Diabetes and Exercise���������������������������������������������������������� 459
Sam N. Scott, Michael C. Riddell, and Jane E. Yardley
Contents
Contents
xiii
26Extreme Sports and Type 1 Diabetes Mellitus in the
Twenty-­First Century: The Promise of Technology���������������������� 483
Karen M. Tordjman and Anthony C. Hackney
27The Endocrine System in Overtraining ���������������������������������������� 495
David R. Hooper, Ann C. Snyder, and Anthony C. Hackney
28Hormones as Performance-­Enhancing Agents������������������������������ 507
Erick J. Richmond and Alan D. Rogol
29Metabolic Syndrome, Hormones, and Exercise���������������������������� 519
Konstantina Dipla, Andreas Zafeiridis, and Karen M.
Tordjman
30Exercise and Training Effects on Appetite-Regulating
Hormones in Individuals with Obesity������������������������������������������ 535
Hassane Zouhal, Ayoub Saeidi, Sarkawt Kolahdouzi,
Sajad Ahmadizad, Anthony C. Hackney,
and Abderraouf Ben Abderrahmane
Index���������������������������������������������������������������������������������������������������������� 563
Contributors
Abderraouf Ben Abderrahmane, PhD Higher Institute of Sport Sciences
and Physical Education of Ksar Saïd, Department of Biological Sciences,
Ariana, Tunisia
Kathryn E. Ackerman, MD, MPH Harvard Medical School, Boston
Children’s Hospital, Department of Sports Medicine and Endocrinology,
Boston, MA, USA
Sajad Ahmadizad, PhD Department of Biological Sciences in Sport and
Health, Faculty of Sports Sciences and Health, Shahid Beheshti University,
Tehran, Iran
Brandon A. Baiamonte, PhD Southeastern
Department of Psychology, Hammond, LA, USA
Louisiana
University,
Claudio L. Battaglini, PhD Department of Exercise & Sport Science, and
Lineberger Comprehensive Cancer Center, University of North Carolina at
Chapel Hill, Chapel Hill, NC, USA
Andrea Silvio Benso, MD, PhD AOU Citta della Salute e della Scienza di
Torino, Division of Endocrinology, Diabetology and Metabolism, University
of Turin, Department of Medical Sciences, Turin, Italy
Chiara Bona, MD AOU Citta della Salute e della Scienza di Torino, Division
of Endocrinology, Diabetology and Metabolism, University of Turin,
Department of Medical Sciences, Turin, Italy
Philip D. Chilibeck, PhD University of Saskatchewan, College of
Kinesiology, Saskatoon, SK, Canada
Naama W. Constantini, MD, DFM Heidi Rothberg Sport Medicine Center,
Department of Sport Medicine, Shaare Zedek Medical Center Jerusalem,
affiliated with the Hebrew University School of Medicine, Jerusalem, Israel
Katherine M. Cooper, BA University of Massachusetts Medical School,
Worcester, MA, USA
Jennifer L. Copeland, PhD Department of Kinesiology, University of
Lethbridge, Lethbridge, AB, Canada
Konstantina Dipla, PhD Department of Sport Science, TEFAA SERRON,
Aristotle University of Thessaloniki, Serres, Greece
xv
xvi
Patricia Katherine Doyle-Baker, DrPH, MA, BSc University of Calgary,
Human Performance Lab, Faculty of Kinesiology, Calgary, AB, Canada
Whitney R.D. Duff, PhD University of Saskatchewan, College of
Kinesiology, Saskatoon, SK, Canada
Alon Eliakim, MD Pediatric Department and Endocrinology Clinic, Meir
Medical Center, Sackler School of Medicine, Tel Aviv University, Department
of Pediatrics, Kfar Saba, Israel
Elizabeth S. Evans, PhD Elon University, Physical Therapy Education,
Elon, NC, USA
Julius E. Fink, PhD Juntendo University Graduate School of Medicine,
Department of Urology, Tokyo, Japan
Allan H. Goldfarb, PhD University of North Carolina Greensboro,
Department of Kinesiology, Greensboro, NC, USA
Silvia Grottoli, MD AOU Citta della Salute e della Scienza di Torino,
Division of Endocrinology, Diabetology and Metabolism, University of
Turin, Department of Medical Sciences, Turin, Italy
Arshpreet Gulati, MD University of Maryland Medical Centre, Mood and
Anxiety Program, Baltimore, MD, USA
St. Elizabeths Hospital, Department of Neurology Consultation Service,
Washington, DC, USA
Anthony C. Hackney, PhD, DSc Department of Exercise & Sport Science,
Department of Nutrition, University of North Carolina, Chapel Hill, NC,
USA
Erik D. Hanson, PhD Department of Exercise & Sport Science, University
of North Carolina at Chapel Hill, Chapel Hill, NC, USA
David R. Hooper, PhD Jacksonville University, Department of Kinesiology,
Jacksonville, FL, USA
Sarah M. Joyce, BExSc Griffith Health Institute, Gold Coast, QLD,
Australia
Jaak Jürimäe, PhD Institute of Sport Sciences and Physiotherapy,
University of Tartu, Tartu, Estonia
Michael Kjær, MD, PhD Department of Clinical Medicine, BispebjergFrederiksberg Hospital, Copenhagen, Denmark
Joanna Klubo-Gwiezdzinska, MD, PhD, MHSc National Institutes of
Health, National Institute of Diabetes and Digestive and Kidney Disease/
Metabolic Disease Branch, Bethesda, MD, USA
Sarkawt Kolahdouzi, PhD Exercise Biochemistry Division, Department of
Exercise Physiology, Faculty of Sport Sciences, University of Mazandaran,
Babolsar, Mazandaran, Iran
Contributors
Contributors
xvii
Robert R. Kraemer, EdD Southeastern Louisiana University, Kinesiology
and Health Studies, Hammond, LA, USA
Fabio Lanfranco, MD, PhD AOU Citta della Salute e della Scienza di
Torino, Division of Endocrinology, Diabetology and Metabolism, University
of Turin, Department of Medical Sciences, Turin, Italy
Kai Lange, MD Department of Clinical Medicine, Bispebjerg-Frederiksberg
Hospital, Copenhagen, Denmark
D. Enette Larson-Meyer, PhD Department of Family and Consumer
Services, University of Wyoming, Laramie, WY, USA
Constance M. Lebrun, MDCM, MPE Department of Family Medicine,
Kaye Edmonton Clinic, Glen Sather Sports Medicine Clinic, University of
Alberta, Edmonton, AB, Canada
Angela Y. Liu, MD University of British Columbia, Department of
Endocrinology, Vancouver, BC, Canada
Anne B. Loucks, PhD Biological Sciences, Ohio Musculoskeletal and
Neurological Institute, Ohio University, Athens, OH, USA
Marco Alessandro Minetto, MD, PhD Division of Physical Medicine and
Rehabilitation, Department of Surgical Sciences, University of Turin, Turin,
Italy
Dan Nemet, MD Child Health and Sports Center, Meir Medical Center,
Sackler School of Medicine, Tel Aviv University, Department of Pediatrics,
Kfar Saba, Israel
Olaoluwa O. Okusaga, MD Baylor College of Medicine, Menninger
Department of Psychiatry and Behavioral Sciences, Houston, TX, USA
Kristin S. Ondrak, PhD Department of Exercise & Sport Science,
University of North Carolina, Chapel Hill, NC, USA
Jonathan Peake, PhD School of Biomedical Sciences, Queensland
University of Technology, Brisbane, QLD, Australia
Moira A. Petit, PhD Activ8, LLC, St. Paul, MN, USA
Teodor T. Postolache, MD University of Maryland Medical Centre, Mood
and Anxiety Program, Baltimore, MD, USA
The Center for Sleep, Mood, Anxiety, and Performance, Washington, DC,
USA
Nunzia Prencipe, MD AOU Citta della Salute e della Scienza di Torino,
Division of Endocrinology, Diabetology and Metabolism, University of
Turin, Department of Medical Sciences, Turin, Italy
Jerilynn C. Prior, BA, MD University of British Columbia, Medicine,
Division of Endocrinology and Metabolism, Vancouver, BC, Canada
xviii
Denis Richard, PhD IUCPQ Research Centre, Laval University, Quebec
City, QC, Canada
Erick J. Richmond, MD, MSc National Children’s Hospital, Pediatric
Endocrinology, San Jose, Costa Rica
Michael C. Riddell, PhD York University, School of Kinesiology and
Health Sciences, Toronto, ON, Canada
Alan D. Rogol, MD, PhD University of Virginia Medical Center, Department
of Pediatrics, Charlottesville, VA, USA
Daniela A. Rubin, PhD Department of Kinesiology, California State
University Fullerton, Fullerton, CA, USA
Ayoub Saeidi, PhD Department of Biological Sciences in Sport and Health,
Faculty of Sports Sciences and Health, Shahid Beheshti University, Tehran,
Iran
Sam N. Scott, PhD York University, School of Kinesiology and Health
Sciences, Toronto, ON, Canada
Abbie E. Smith-Ryan, PhD Department of Exercise & Sport Science,
University of North Carolina, Chapel Hill, NC, USA
Ann C. Snyder, PhD University of Wisconsin – Milwaukee, Department of
Kinesiology, Milwaukee, WI, USA
John W. Stiller, MD Neurology Consultation Service, St. Elizabeths
Hospital/DC Department of Behavioral Health, Department of Neurology,
Washington, DC, USA
David H. St-Pierre, PhD University of Quebec at Montreal (UQAM),
Montreal, QC, Canada
Joi J. Thomas, MS Department of Athletics, University of Wyoming,
Laramie, WY, USA
Karen M. Tordjman, MD Tel Aviv Sourasky Medical Center, Affiliated to
the Sackler Faculty of Medicine, Tel Aviv University, Institute of
Endocrinology, Metabolism, and Hypertension, Tel Aviv, Israel
Johannes D. Veldhuis, MD Endocrine Research Unit, Mayo Clinic,
Rochester, MN, USA
Charles E. Wade, PhD Center for Translational Injury Research (CeTIR),
Houston, TX, USA
Leonard Wartofsky, MD Thyroid Cancer Research, Georgetown University
School of Medicine, MedStar Health Research Institute, Department of
Endocrinology, Washington, DC, USA
Jane E. Yardley, PhD University of Alberta, Augustana Faculty, Camrose,
AB, Canada
Contributors
Contributors
xix
Dorina Ylli, MD, PhD MedStar Health Research Institute, Thyroid Cancer
Research Center, Washington, DC, USA
Kohji Yoshida, MD Department of Obstetrics and Gynecology, University
of Occupational and Environmental Health, Kitakyushu, Japan
Andreas Zafeiridis, PhD Department of Sport Science, TEFAA SERRON,
Aristotle University of Thessaloniki, Serres, Greece
Hassane Zouhal, PhD Univ Rennes, M2S (Laboratoire Mouvement, Sport,
Santé), Rennes, France
1
Methodological Considerations
in Exercise Endocrinology
Anthony C. Hackney, Abbie E. Smith-Ryan,
and Julius E. Fink
Introduction
Over the last several decades, an increasing number of exercise science investigations have incorporated measurements of endocrine function
(e.g., hormones, cytokines) into their research
designs and protocols [1, 2]. This approach has
allowed for a heightened level of investigation
into research which examines the physiological
mechanisms associated with clinical and
performance-­related conditions found in individuals involved in exercise training.
Some exercise science investigations, however, have not always controlled certain critical
factors (e.g., time of day for blood sampling,
level of chronic training, etc.) that can influence
many of the hormones associated with the human
endocrine system. This lack of investigative control has often resulted in the resulting research
findings to be inconsistent, contradictory, and
A. C. Hackney (*)
Department of Exercise & Sport Science,
Department of Nutrition, University of North
Carolina, Chapel Hill, NC, USA
e-mail: ach@email.unc.edu
A. E. Smith-Ryan
Department of Exercise & Sport Science,
University of North Carolina, Chapel Hill, NC, USA
J. E. Fink
Juntendo University Graduate School of Medicine,
Tokyo, Japan
sometimes extremely difficult to interpret. This
insufficient control of biological experimental
factors appears to be due in part to limited
knowledge by exercise science researchers in the
area of clinical endocrine methodology and
techniques.
Experts suggest that the factors that influence
hormonal measurements, and contribute to variance in experimental outcomes, can be categorized as consisting of two potential sources:
factors affecting physiological variation (i.e.,
affiliated with the physiological function status
of the subject) and factors affecting procedural-­
analytical variation (i.e., determined by the investigators conducting research) [1, 3]. Regardless
of the source of variance, subject, or investigator
derived, if it is not controlled or accounted for
appropriately, the resulting hormonal measurements obtained can be compromised and thus
call into question the scientific validity of a
research study.
The focus of this chapter is to provide background information for exercise science researchers on those physiological-procedural-analytical
factors that can potentially affect endocrine measurements. The intent is for this material to serve
as an introductory “fundamental coverage” on
this topic in hopes of improving the quality of
research in exercise endocrinology.
The field of endocrinology uses numerous
abbreviations for the many of the hormones that
exist. To aid those researchers unfamiliar with
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_1
1
A. C. Hackney et al.
2
Table 1.1 The following are abbreviations commonly
used for various hormones seen in exercise science and
sport medicine endocrinological research (see Ref. [4])
Sex/Gender
It appears that until the onset of puberty, there is
little difference between males and females in their
resting hormonal profile. Once puberty is reached
though, there is increased androgenic steroid hormone production in the male, and the female starts
the characteristic menstrual cycle pulsatile release
of gonadotropin and sex steroid hormones [5–7].
Additionally, at puberty, resting leptin (an adipocyte cytokine; a low molecular weight protein that
has endocrine-like actions on select physiological
process such as the immune system [8]) levels tend
to become increased in females, as compared to
those in males [9]. In adulthood, the hormonal differences that begin to manifest at puberty tend to
remain until females reach the postmenopausal
period and males reach andropause [8, 9].
There are some sex-specific differences in the
hormonal responses to exercise in males and
females. These include an earlier and greater rise
in testosterone and creatine kinase during exercise and up to 24 hours after exercise in males as
compared to females [1, 10, 11] and a greater
pre-exercise growth hormone response in
females. Furthermore, the magnitude of the sex
steroid hormonal response to exercise in females
is influenced by the status and phase of their
menstrual cycle [10, 12]. Interestingly, the menstrual cycle hormones can influence other hormones and their response to exercise (e.g.,
this lexicon, Table 1.1 lists those abbreviations increased estradiol-β-17 → increases growth horfor the most common hormones associated with mone levels) [10–13] (see later discussion conthe area of exercise science [4].
cerning the menstrual cycle in this chapter, as
well as Chap. 16 in this book). On the other hand,
some hormones show little or no differences in
response to exercise between the sexes (e.g.,
Physiological Factors
water balance hormones such as aldosterone and
As mentioned, factors that can influence hor- arginine vasopressin) [5, 10, 12].
Due to these potential differences in outcomes
monal measurements can be categorized into two
broad areas: “physiological” and “procedural-­ due to sex, the researcher should be cautious
analytical.” The physiological factors are those when using adult subject populations involving a
that are determined to be connected in some way mixture of males and females in their studies. To
to a biological function or status of the research avoid confounding results, researchers need to be
subject (patient) at the time of the collection of the certain that the hormonal outcomes they are measpecimen (e.g., blood) to be analyzed. These are suring are not influenced by sex/gender and stage
factors that can be viewed as pertaining to a vari- of menstrual cycle, as will be discussed in subsequent sections of this chapter.
ety of endogenous aspects of the subject/patient.
Name
Adrenocorticotropic hormone
Aldosterone
Antidiuretic hormone
Atrial natriuretic peptide
Arginine vasopressin
β-Endorphin
Catecholamines
Corticotropin-releasing hormone
Cortisol
Epinephrine
Estradiol-β-17
Follicle-stimulating hormone
Glucagon
Gonadotropin-releasing hormone
Growth hormone
Growth hormone-releasing hormone
Insulin
Insulin-like growth factor [1]
Leptin
Luteinizing hormone
Norepinephrine
Parathyroid hormone
Progesterone
Prolactin
Reverse triiodothyronine
Testosterone
Thyrotropin-releasing hormone
Thyroid-stimulating hormone
Thyroxine
Triiodothyronine
Abbreviations
ACTH
ALD
ADH
ANP
AVP
β-END
Cats
CRH
CORT
EPI
E2
FSH
GLU
GnRH
GH
GHRH
IN
IGF1
LP
LH
NEPI
PTH
P
PRL
rT3
TEST
TRH
TSH
T4
T3
1
Methodological Considerations in Exercise Endocrinology
Age
If subjects are not matched for age and maturity
level, whenever possible, variance in the outcomes can be potentially increased. For example, a prepubertal and postpubertal child (of the
same gender) will not typically display the exact
same hormonal exercise responses or relationships [14, 15]. This is illustrated by the welldocumented increase in insulin resistance which
is observed as an adolescent goes through
puberty [16].
This concern should also be extended to the
other end of the age spectrum. That is, a postmenopausal female or andropausal male could
have drastically different hormonal responses
when compared to a relative prepausal individual. For example, basal growth hormone and testosterone typically decrease with age, while
cortisol and insulin resistance increase [17–19].
These types of age-related differences cannot
only exist at rest, but also in response to exercise,
and even after completing an exercise training program. As an illustration, a study by Brook et al.
showed that the anabolic responses to resistance
training are impaired within the elderly, possibly
due to lower testosterone levels (young subjects = 367 ± 19; old subjects = 274 ±
19 ng•dl−1), ribosomal biogenesis (RNA:DNA ratio
and c-MYC induction; young = +4 ± 2-fold change;
old = +1.9 ± 1-fold change), and/or translational
efficiency S6K1 phosphorylation (young =
+10 ± 4-fold change; old = +4 ± 2-fold change) (see
Chap. 21 in this book concerning S6K1 [mTOR
substrate S6 kinase 1]) [20]. For this reason, it is
important to match subjects in research studies by
chronological age and/or maturation level in order
to increase the homogeneity of the responses and
decrease interindividual variability, obviously, that
is, unless the researcher is trying to study agerelated changes among groups of individuals [3].
Ethnicity and Race
A variety of different humoral constituents are
known to vary between people of different races
and ethnic groups [1, 3]. For example, resting
3
parathyroid hormone levels tend to be higher in
Black compared to Caucasian individuals [21].
Caucasian females tend to have higher levels of
estrogens than Asian females [1, 22]. Evidence
also suggests that reproductive hormone levels
during gestational periods may vary greatly
across several races and ethnic groups
(Caucasians, Blacks, Latinos, Asians, and
Indians) [22–25]. Findings of greater resting
insulin and degree of insulin resistance in certain
Native American tribes (e.g., Pima Indians) have
also been reported; however these differences
may in fact be more related to obesity issues in
these individuals [26]. Testosterone levels seem
also to have differences among ethnicities, with
Asian- and Indian-related ethnicities showing
slightly lower levels as compared to other ethnicities [27].
Hormonal responses to exercise and exercise
training related to race and ethnicity have not
been well studied, and the limited available findings do not suggest drastically different response
outcomes beyond basal differences. Further
research is certainly necessary and warranted in
this area [1, 25, 26].
Body Composition: Adiposity
The level of adiposity of the body can greatly
influence the release of certain cytokines by
adipose tissue [3, 8, 9]. These cytokines in turn
can have autocrine-, paracrine-, and endocrinelike actions and influence aspects of metabolism, reproductive, and inflammatory function
[2, 3, 8, 9]. For example, increase in adipose
tissue raises the expression of aromatase, triggering higher conversion rates of testosterone
to estradiol, triggering a negative feedback to
the pituitary gonadotropin secretion, and ultimately resulting in lower testosterone levels
[28]. Additionally, several of these cytokines
have been directly linked to the promotion of
increased hormonal levels (e.g., increased
interleukin-6 → increased cortisol) [8]. This
situation becomes compounded as adiposity
reaches the level of obesity and subsequently
affects many hormones to a far greater degree.
A. C. Hackney et al.
4
For example, insulin and leptin levels tend to be
appreciably elevated at rest in many obese persons [29–33].
As levels of adiposity increase, the hormonal
response to exercise and exercise training can
change considerably from that of a normal-­
weight person. As an illustration, in obese persons, catecholamine and growth hormone
response to exercise becomes blunted [33].
Cortisol responses to exercise seem to become
elevated in some overweight-obese individuals,
although isolated cases have shown cortisol
responses have been shown to be blunted and
reduced [32, 33]. Exercise training often allows
a loss of body mass, in particular fat mass, which
helps to normalize these hormones with levels
observed in normal-weight people [33–37].
To ensure that varying levels of body composition of subjects will not confound hormonal
outcomes, investigators need to match their subjects for adiposity as closely as possible and not
just use body weight matching as criterion.
Exactly how close of a match is needed is not
known, but grouping normal-weight, overweight
(body mass index (BMI) ≥ 25.0–< 30.0 kg/m2),
and obese (BMI ≥ 30.0 kg/m2) individuals into
the same subject group can most certainly complicate and add variance to some hormonal outcomes [1, 33].
Disease States
Several disease conditions such as HIV, testicular cancer, hormonal disorders (e.g., Cushing’s
syndrome, Graves’ disease, etc.), infections,
chronic liver or kidney diseases, type 2 diabetes,
and obesity have been shown to affect hormones;
e.g., lower sex hormone levels [38, 39].
Specifically, infection-type diseases may lead to
testicular dysfunction, and metabolic conditions
may lead to hypogonadism via increased adipose
tissue and inflammation [28]. Indeed, in HIVinfected patients, lymphoma, or syphilis effects
on the pituitary, can trigger or mimic apoplexy
and meningeal or pituitary infection leading to
fibrosis and ultimately dysfunction [40].
Increased adipose tissue often observed in obese
and patients with type 2 diabetes leads to
increased aromatization activity converting testosterone to estradiol, leading to a negative feedback to the pituitary gonadotropin secretion
triggering hypogonadism [28]. Many individuals
are unaware of these conditions when signing up
for a study; therefore thorough medical screening is an important consideration.
Mental Health
Select mental health conditions and states are
associated with high levels of anxiety and apprehension (e.g., posttraumatic stress disorder),
which can lead to enhanced activity of the sympathetic nervous system and hypothalamic-­pituitary-­
adrenal axis [41–43]. Subsequently, resting levels
of circulating catecholamines, adrenocorticotropic hormone, β-endorphin, and cortisol can be
elevated. In contrast, persons who are experiencing depression can have low arousal levels, and
the abovementioned hormones could be suppressed. Moreover, depression is sometimes
accompanied by low activity levels in the hypothalamic-pituitary-thyroid axis (i.e., low thyrotropin-releasing
hormone,
thyroid-­
stimulating
hormone, thyroxine, and triiodothyronine) creating a euthyroid sick syndrome response [41–43].
These alterations in resting hormonal levels from
such conditions can in turn result in altered hormonal responses to exercise and exercise training
in individuals who have high levels of anxiety
[44–46]. In some cases this can result in heightened responses (excessive) or diminished
responses [44–46]. Evaluating the mental health
status, via the completion of a screening questionnaire by a participant, can serve as an excellent
tool to determine if a potential emotional or psychological problem exists which could confound
hormonal measurements. A variety of such
screening tools are available, and the reader is
directed to several excellent references for overviews of this topic [47, 48]. Importantly, it is
highly advisable that any such assessment be performed by a trained, qualified individual.
1
Methodological Considerations in Exercise Endocrinology
Menstrual Cycle
Menstrual status (eumenorrheic vs. oligomenorrheic vs. amenorrheic) and cycle phase (follicular,
ovulation, luteal) in females can produce basal
changes in key reproductive hormones such as
estradiol-β-17, progesterone, luteinizing hormone
(LH), testosterone, and follicle-stimulating hormone (FSH). These changes can be large and dramatic within select individuals. For example, the
ovulatory and luteal phases result in increases in
all of the aforementioned hormones above what is
seen in the follicular phase (e.g., 2–10-fold greater
in eumenorrheic female) [49]. These typical
changes are depicted in Fig. 1.1. As noted earlier,
select reproductive hormones (sex steroids) at rest
can influence certain other nonreproductive hormones and nonreproductive physiological function such as estradiol-β-17 enhancing growth
hormone release and thus subsequently increased
lipid metabolism [11, 50, 51].
The menstrual status and cycle phase hormonal influences can carry over to have an impact
on exercise and exercise training responses, too.
Consequently, researchers may need to conduct
exercise testing with females of similar menstrual
status and/or in similar phases of their cycle. This
precaution is also applicable to females who are
using oral contraceptives, which can mimic some
hormonal fluctuations similar to cycle phase
changes [51, 52]. The precise impact of oral conceptive (OC) depends upon the composition of
the OC used (mono-, bi-, or triphasic) and the
dosage of the active estrogen and progestin
agents in the pharmaceuticals.
It is also an important consideration when
there is an absence of a menstrual cycle either
due to amenorrhea (especially hypothalamic
based) or due to pregnancy, this absence leads to
changes in hormonal levels and exercise
responses [1, 2, 24].
Circadian Rhythms
Over the course of a 24-h period, many hormonal
levels will fluctuate and display circadian variations (see Chap. 20 of this book). In some cases
these variances are due to pulse generator aspects,
which is the spontaneous release of select hypothalamic hormonal releasing factors/hormones
[53] within the endocrine regulatory axis. In
other cases, variances are related to humoral
stimuli, changes brought on by individual behavior or environmental factors, and these humoral
stimuli influence hormonal release [54, 55].
Circadian hormones can display dramatic
changes in levels due to their rhythm patterns,
cortisol being a prime example. Morning cortisol
levels are typically twice that of those found later
Pituitary hormones = LH, FSH
Ovarian hormones = Estrogen
Progesterone
Relative Hormonal Changes
Fig. 1.1 Typical
hormone changes
(arbitrary scaling for
concentration changes)
associated with the
menstrual cycle in
eumenorrheic women
5
LH
Progesterone
Day
1
Menses
(~ 3-5 days)
Estrogen
FSH
Day
14
Ovulation
Follicular Phase
Day
28
Luteal Phase
A. C. Hackney et al.
6
Table 1.2 Hormones that display discernable circadian patterns. The arrows indicate a relative direction for changes
in concentration levels
Hormone
ACTH
Aldosterone
Cortisol
AM
concentration
↑ Early AM
↓
↑↑
PM
concentration
↓
↑
↓↓
Growth hormone
LH-FSH
↑ Early AM
↓↑
↓
↓↑
Melatonin
Parathyroid
hormone
Prolactin
↑ Early AM
↓
↓
↑
↑ Early AM
↓ Late AM
↑
↑
↓
Testosterone
Remarks
Highest levels may be during sleep
Highest levels may be during sleep
Influenced by food intake; highest levels may be during
sleep
Only slight differences; highest levels may be during sleep
Pulsatility or release and menstrual cycle phase override
circadian pattern
Highest levels may be during sleep
Highest levels may be during sleep
Highest levels may be during sleep
Lessens with age
Arrows indicate an increase (↑) or decrease (↓) in hormone concentration
in the day [56–58]. Table 1.2 provides some reference on the circadian pattern seen in some key
hormones.
These fluctuations and circadian variations
need to be addressed when conducting exercise
research. Studies demonstrate that the magnitude of exercise responses may not be similar
at different times of the day, even if the exercise intensity and duration are held constant [1,
56]. Investigators should plan accordingly so
as to more carefully control and replicate the
time of day in which research evaluations are
conducted and hormonal specimen collected
[59, 60].
otal Versus Free Hormone
T
Concentration
A number of hormones exist in the circulation as
either in there free or total amounts forms, the
latter being the sum of the free and the carrierbound portion of the hormone. Steroid hormones
are the principal example of this situation. Some
investigators do not completely recognize this
point and in conducting their research at times
measure the wrong form of the hormone in question. A prime illustration of this is the hormone
testosterone in which the free form is viewed as
more biologically active.
That is, the major part of circulating testosterone binds to sex hormone-binding globulin
(SHBG) and some to albumin, leaving only a
small fraction of testosterone as free form. In order
to be bioactive, testosterone has to be unbound,
making only free and albumin-bound (weak bound
easy to dissociate) available for tissue uptake. It
has been debated for a long time which form of
testosterone (total vs. free) is a better indicator for
testosterone levels in subjects. A recent study demonstrated that even if total testosterone levels are
normal, low free testosterone is associated with
hypogonadal signs and symptoms. This suggests
free testosterone might be a more accurate measure of androgen-related conditions as compared
to total testosterone, although clinicians/researchers must make their own determination on which
hormonal form they should be accessing [61].
Procedural-Analytical Factors
The second category of factors influencing hormonal measurements is made up of those factors
that have procedural or analytical aspects to them.
These factors are determined, selected, or in some
way potentially controlled for by the investigators
conducting or the participant involved with the
research [1]. These factors can be viewed as exogenous relative to their influence.
1
Methodological Considerations in Exercise Endocrinology
Ambient Environment
When conducting research investigations, it is
important to remember that excessive exposure to
hot or cold ambient temperatures can stimulate the
release of various hormones, e.g., those involved
in water balance (aldosterone) or energy substrate
mobilization (cortisol) [44, 62, 63]. Even elevated
ambient relative humidity (water vapor) can
induce this effect, primarily due to a compromised
heat dissipation through reduced evaporative efficiency adding to the body core temperature [63].
These effects can be further augmented if hypoxemia is induced along with temperature extremes
(e.g., mountain climbing), as can occur when
moving to higher elevations and being exposed to
greater degrees of hypoxia [64–66].
Many of the exercise and exercise training
hormonal responses are tremendously impacted
by environmental factors. In particular, catecholamines, growth hormone, aldosterone, arginine vasopressin, adrenocorticotropic hormone,
and cortisol are all susceptible to changes in
environmental conditions and show highly
exacerbated responses in such varying conditions [1, 44, 62, 63].
To minimize these influences, it is critical to
conduct exercise testing in controlled, standardized conditions such as in a laboratory. On the
other hand, if conducting field research (where
environmental standardization can be impossible), then it is important to measure/record environmental factors and convey them in any
subsequent reporting of the data in the literature.
Nutrition
The nutritional status and practices of a research
subject, including food composition, caloric
intake, and timing of meals, can greatly impact
the hormones associated with energy substrate
mobilization and utilization (e.g., insulin, glucagon, epinephrine, growth hormone, insulin-like
growth factor, cortisol) [1, 67, 68]. The exact
nature of the effect (augmented or attenuation)
depends on the interaction of the nutritional fac-
7
tors just mentioned and how severely the alterations are from the normal nutritional regimes of
the individual [1, 33, 41].
The hormones noted above are critical during
exercise to ensure that energy metabolism meets
the demands of exercise. Thus, altered dietary
practices and nutrition status of a subject can
alter energy substrate (glycogen) storage and
availability [68–70]. This in turn can cause the
hormonal response to exercise to vary to some
degree. For example, Galbo and associates demonstrated that the glucagon, epinephrine, growth
hormone, and cortisol response to exercise were
greater when a low-carbohydrate, high-fat diet is
consumed (i.e., 4 days of consumption) compared to a normal mixed diet [67].
Normally in clinical settings, it is recommended that subjects be fasted prior to blood hormonal evaluations (e.g., 8 h). It is not always
practical, however, for athletes to comply with
such request due to their high demand for adequate caloric intake to maintain energy balance,
anabolism, and muscle glycogen reserves.
Therefore, a modified fasted approach may be
necessary for this special population such as only
a 4–6-h fast. Even with the constraints of working around an athlete’s special needs, it is still
advisable that exercise investigators try to control
and standardize the dietary practices of their subjects as much as possible to mitigate the effects of
differing diet between subjects, and within an
individual subject’s diet, if a repeated measures
research design is being used [41, 67].
Nutrient Timing
The concept of nutrient timing is arguably one of
the most important aspects to account for when
designing a study and evaluating results [71]. The
evaluation of timing food consumption has been
shown to influence muscle morphology outcomes
directly and indirectly by stimulating hormone
secretion [72]. As coined by Dr. John Ivy, the
nutrient timing system accounts for three phases:
the energy phase, anabolic phase, and growth
phase [71]. Additional consideration should be
given to the pre-exercise phase, which can largely
influence the endocrine response during and
8
A. C. Hackney et al.
can enhance muscle glycogen resynthesis and is
enhanced with a protein/carbohydrate combination [72, 79]. A carbohydrate-amino acid supplement influenced testosterone and cortisol levels
120 min after intake and exercise [80]. However,
post-exercise nutrient consumption consumed
later following exercise (i.e., 8–9 h) has demonPre-exercise Cortisol levels, which help to strated no hormonal influence [81]. Intake of carmaintain the integrity of the immune system, are bohydrates + protein + vitamins post-exercise
strongly influenced by glucose availability [73– has been shown to reduce free radicals and main75]. Additionally, acute carbohydrate intake can tain immune function. This may be a considerstimulate an increase in insulin and glucose lev- ation for researchers evaluating exercise and
els, sparing muscle glycogen as well as reducing immunology characteristics, as well as various
cortisol levels. Acute consumption of a glucose-­ aspect of overtraining.
electrolyte solution (GES) prior to exercise has
been shown to significantly reduce cortisol lev- Meal Frequency and Patterning
els, when compared to water. Allowing a subject Meal frequency and overall caloric consumpto consume a carbohydrate drink before testing, tion may also influence metabolic-hormonal
independent of amount (e.g., 25 g vs. 200 g), may markers, such as C-reactive protein, fasting
significantly maintain glucose and cortisol levels plasma glucose, insulin, as well as total cholespost-exercise, as well as stabilizing the neutro- terol [82, 83]. In as much, investigators may
phil to lymphocyte ratio [75]. Pre-exercise vita- consider questioning participants about food
min consumption, or an antioxidant enhanced consumption patterns or utilize a food frequency
beverage, may protect against acute tissue dam- questionnaire.
age augmenting exercise adaptations and when
consumed chronically may maintain immune Eating Disorders
The eating disorder “anorexia nervosa” is a spesystem markers [76].
cial concern relative to nutrition status due to its
Anabolic Phase (During Exercise) Carbohydrate profound effect on the endocrine system [1, 52,
supplementation during exercise has also been 84]. Anorexics tend to have lower resting luteinassociated with a blunted cortisol, growth hor- izing hormone, follicle-stimulating hormone, and
mone, and cytokine response while also main- estradiol-β-17 levels [84]. Anorexia also affects
taining glucose levels and insulin stability [77, the pituitary-thyroid-glandular axis. Specifically,
78]. There is additional evidence demonstrating the condition is associated with suppression of
reduced T cell and NK cell levels with carbohy- triiodothyronine, somewhat decreased thyroxine,
drate feeding during exercise [77]. Acute, uncon- elevation of reverse triiodothyronine, and, occatrolled feedings should be accounted for when sionally, decreases in thyroid-stimulating horestablishing a study design as well as potential mone [84]. Such a thyroidal state is referred to as
confounders when interpreting immune function the “euthyroid sick syndrome” and can accomresults. Protein consumption during exercise pany severe body weight loss [3, 52, 84]. There is
blunts protein degradation and has a sparing also an effect on the adrenocortical axis, with
effect on muscle glycogen [72].
higher levels of cortisol due to an increased liberation of corticotropin-releasing hormone [84].
Growth Phase (Post-exercise) Immediate post-­ Growth hormone is also increased, although
workout fuel consumption has the potential to insulin-like growth factor-1 levels (which facilihighly influence muscle machinery by utilizing tate the physiological actions of growth hormone)
the anabolic characteristics of insulin. are suppressed in the anorexia condition [84].
Additionally, an increase in insulin post-exercise Due to the psychological aspects of the anorexia
post-exercise. Although most research protocols
hold diet constant, considerations for what the
subject consumes before and after, ad libitum,
may have substantial influences on acute and
chronic adaptations, in part due to the stimulation
of hormones.
1
Methodological Considerations in Exercise Endocrinology
nervosa (see Refs. [85, 86]), this condition could,
in the context of the organization of this chapter,
be also discussed with mental health issues. Thus
this factor could also be considered of a biological nature and consequently has powerful effects
on a multitude of endocrine measurements.
9
[92, 93]. If inadequate amounts of time have
elapsed (lack of recovery), some hormonal
responses at rest, or in the subsequent exercise
testing, can be attenuated and others augmented.
Furthermore, the magnitude of this effect can be
influenced by the exertion required of the prior
exercise (e.g., high-intensity intervals require
longer recovery).
Stress-Sleep
If possible, researchers may require a 24-h
recovery prior to a subject reporting to the laboEmotional stress and/or sleep deprivation are ratory for testing. However, subjects who are
each known to affect certain hormones within the athletes may find it difficult to reduce their
endocrine system. For example, emotionally dis- training or miss a workout session for experitraught individuals will typically have elevated mental purposes in research studies. A modified
basal catecholamine, growth hormone, cortisol, approach may be necessary, such as only a 12and prolactin levels [1, 87–89]. Those hormones or 8-h recovery period, because this could somewith circadian patterns (see Circadian Rhythm what prevent stress and anxiety (which as noted
section; e.g., luteinizing hormone, follicle-­ can affect the endocrine system) in the athlete
stimulating hormone, adrenocorticotropic hor- since they would be missing less training time
mone, cortisol) can be shifted in their [1, 93–95].
characteristic pattern-rhythm by disruption of
A powerful influence on resting and exercise
sleep cycles [43, 46, 87–91].
hormonal response of a subject is the exercise
These types of factors (i.e., stress, sleep depri- training status—that is, trained vs. sedentary. The
vation) can also influence the hormonal response more “trained” a subject is, typically the greater
to exercise and exercise training. Investigators the effect on the neuroendocrine system. Many
must attempt to control these factors whenever hormones show attenuated resting and submaxipossible. In fact, it is advisable to have a pre-­ mal exercise responses in trained individuals,
exercise questionnaire completed by a subject to although some can actually be augmented (e.g.,
monitor and evaluate the level of these factors, testosterone in resistance-trained individuals) in
and if a predetermined status is not obtained, then response to submaximal and maximal exercise
hormonal measures and exercise testing should [2, 96–100].
be rescheduled.
Besides acute effects of physical activity on
As a footnote to this issue, many investiga- hormonal levels, chronic endurance exercise
tions in the exercise area use college students as such as distance running, cycling, race walking,
research subjects. Such students can have high and triathlon has been shown to put immense
levels of emotional stress due to their education stress on the endocrine system, many times
demands (e.g., examination periods, projects resulting in the suppression of some hormones
being due, oral reports). Care should be taken to [9]. This phenomenon may be related to the
not utilize student subjects when there are in high “overtraining syndrome” (see Chap. 27 of this
emotion stress periods as a multitude of hor- book). The exact mechanism of hormonal reducmones can potentially have very atypical values tion following chronic strenuous endurance
and responses [43].
exercise is not elucidated yet; however an impairment of the hypothalamic-­
pituitary regulatory
axis due to energy decreases is postulated by
Physical Activity
some researchers [101].
An extensive dialogue on the influence of
The proximity in time between exercise sessions exercise training on hormonal profiles at rest and
can affect the hormonal profiles of individuals in response to exercise is beyond the scope of this
10
chapter, but the reader is directed to Refs. [2, 3]
for more in-depth discussions.
Subject Posture-Position
There are changes in the plasma volume component of the blood as a subject changes position.
Standing upright results in a reduction of plasma
volume compared to a recumbent position [102].
These shifts in the plasma fluid are in response to
gravitation effects as well as alterations in capillary filtration and osmotic pressures [102]. Large
molecular size hormones, or ones bound to large
weight carrier proteins, could be trapped in the
vascular spaces; this means that a loss of plasma
fluid would increase the concentration of these
hormones (hemoconcentration). Conversely, a
gain of plasma fluid would decrease the concentration of these hormones (hemodilution) [44,
103]. These adjustments in fluid volume to move
in or out of the vascular space due to posture
shifts typically require approximately 10–30 min
[102, 103].
In exercise research situations where blood is
drawn to assess hormones, it is recommended
that the condition of specimen collection related
to the subject’s position be controlled and
reported in publications. This type of information is most certainly necessary if a postural
change is occurring for a 10-min or greater duration [58, 103].
Specimen Collection
Suitable precautions must be taken in the collection and storage of blood specimens to ensure
they are viable for later hormonal analysis. In
clinical and exercise-related blood work, venous
blood is the specimen usually utilized. If the
blood specimen is being obtained by venipuncture, it is important to not have the tourniquet on
the subject’s arm too long (∼1 min or longer).
Greater lengths of time can result in fluid movement from the vascular bed due to increased
hydrostatic pressures [103]. Once collected, the
A. C. Hackney et al.
blood sample should be centrifuged at ∼ 4 °C in
order to separate the plasma (collection tube contains anticoagulant) or allowed to clot (collection
tube is sterile) then centrifuged for serum. If centrifugation cannot be done immediately, then the
blood sample should be placed on ice, but it is
more prudent to centrifuge without delay. Once
separated, the plasma/serum should be aliquoted
and stored at a temperature of −20 to −80 °C
until later analysis. Care should be given to
ensure certain plasma/serum is stored in airtight
cryofreeze tubes (screw-cap type is recommended), which allow for a longer storage period.
It is also advisable to split up specimens into several aliquots if multiple hormonal analyses are
going to be conducted. Once a sample is thawed,
it has a relatively short “shelf life” in a refrigerator, and repeated unthawing and refreezing cycles
can degrade certain hormonal constituents and
compromise the validity of the analysis [104–
106]. Care should be taken to ensure that the
assay procedures employed are specific for
plasma or serum, as in some cases these cannot
be used interchangeably in the assay (e.g., adrenocorticotropic hormone is measured in plasma).
Furthermore, an examination of the research literature may be necessary to determine if one
form of blood component is more popular or
prevalently used in research.
In blood specimens, either plasma or serum is
utilized for biochemical analysis, but some hormonal measures can also be made in urine and
salivary samples. In general plasma and serum
give very similar values for hormonal analytes,
and seldom is one considered better than the
other in blood analysis [105, 106]. Be aware,
however, specific assay procedures do, in some
situations, have a preferred blood fluid for analysis. Thus it is critical for the researcher to know
what each hormonal assay requires as the analyte
and then plan accordingly. This type of information is provided by the manufacturer of the analytical supplies-components used in the assay
procedures.
With respect to urine and saliva, they are
attractive as specimens to collect because of their
noninvasive nature. They do, however, have cer-
1
Methodological Considerations in Exercise Endocrinology
tain drawbacks. Urine analysis tends to be limited primarily to steroid-based hormones, and
there is usually a need to collect 24-h urine specimen. The collection of 24-h urine specimens can
be a tedious and demanding process for the subject. Also, urine measurements may not always
be reflective of “real-time” hormonal status
either, as urine can sit in the bladder for hours
before being voided. Saliva allows for easier
sampling procedure and can reflect hormonal status in a more real-time fashion. However, saliva
also primarily only allows for steroid hormonal
assessments (i.e., constituents that can cross from
the blood into the salivary gland) [107].
Furthermore, saliva is limited to free hormonal
concentrations as the protein-bound constituents
typically cannot pass through the salivary gland
due to their large molecular size. Research does
suggest that the blood and saliva levels of hormones can mirror each other in their relative
changes, but not perfectly, as correlation coefficients of only 0.7–0.8 are typically found [1, 104,
107]. Researchers must determine if these limitations preclude the use of these biological fluids in
their studies [104, 107–109].
Analytical Assays
A variety of biochemical analytical methods (i.e.,
“assays”) exist for measuring hormones in biological specimens. Chromatographic, receptor,
and immunological assays are all available.
Perhaps the most prevalent contemporary technique in use is immunological assays, which have
variations such as chemiluminescence immunoassay (CLIA), radioimmunoassays (RIA),
enzyme immunoassays (EIA), enzyme-linked
immunoassays (ELISA), and electrochemiluminescence immunoassays (ECLIA) [109–111].
Each of these techniques has its strengths and
weaknesses, and the discussion of each is beyond
the scope of this chapter, but the reader is directed
to Refs. [112–114] for more background and
explanation about this subject.
Researchers should always know the particular aspects of the hormonal assay techniques they
11
plan to use in their studies. Specifically, it is
important they be aware of the precision of the
assay (“how accurate is it?”), sensitivity of the
assay (“how small of a change can it detect?”),
and the specificity of the assay (“how much
cross-reactivity is there with similar looking
chemical structures in the specimen?”). Ideally
the researcher wants the most precise, highly sensitive, and specific assay they can obtain, but cost
considerations can impact decision-making in
these matters. It is advisable for the researcher to
report precision, sensitivity, and cross-reactivity
values in publications to allow readers to determine the quality of the analytical techniques and
procedures of the assays that were used.
Additionally, it is desirable to report in publications the coefficient of variation (CV) “within”
an assay and “between” an assay for each respective hormone measured. This will allow the
reader to determine how well the analytical technical procedures were carried out [114, 115].
One step to mitigate the potential between-assay
CV is to collect and analyze your biological samples in batches of specimens and not as isolated
specimens on a day-by-day basis. However, caution is necessary here as batches that are too large
can influence your outcome by creating “end of
run effects” within the assay. That is, running
such a large number of samples in a single batch
that the precision of the technician performing
the assay may be compromised (i.e., procedural
fatigue), or the kinetics of the specific assay may
be influenced by the length of time it takes to
pipette the various components in assay (i.e., in
adding the chemical reagents to the first sample
tubes vs. the last tubes; too much time has transpired, resulting in different lengths of time for
chemical reactions to take place within the specimen tubes) [114, 115].
Data Transformations
Before conducting statistical analysis on hormonal data measured within the assays, it may be
necessary to transform the data. Two of the most
common endocrine transformations usually seen
A. C. Hackney et al.
12
in literature are (1) expressing the data as a percent change from some precondition (i.e., before
exercise), basal value, and (2) conducting a logarithmic conversion of the data. The first is
­typically done to account for relative changes in
hormonal concentrations when absolute magnitude of change may be misleading. For example,
a cortisol change from 276 to 331 nmol/L is
highly different from a 55–110 nmol/L (20% vs.
200%) even though the absolute magnitude is
identical. A 200% increase in the hormonal concentration may have many more profound physiological effects than the smaller percentage. In
the second form of transformation, logarithmic
transformation is normally performed due to a
large degree of variance in the subject data resulting in a nonnormal distribution. This can be due
to sample size issues, variance with the analytical
technique, or the physiological nature of the hormone being studied. Despite the transformation
used, it is vital that the researcher report to the
reader in the publication if and how the data were
manipulated prior to conducting the statistical
analysis (and what was the rationale for performing the transformation) [109, 116].
A third data transformation that is less frequently used is the area under-the-curve (AUC)
procedure. This is carried out when there are
serial specimen samples (repeated measures
design) from a subject. These serial values are
plotted, and then an integration of the area under
the plotted responses curve is determined, thus
collapsing numerous data values into one
response and potentially eliminating some of the
variability associated with having many hormonal measurements [117]. This approach is
favored by some researchers; their rationale is the
overall response of the hormone, and gland in
question can be better quantified. Nonetheless,
the procedure can be influenced by the number of
serial samples collected to determine the response
curve as well as the circadian rhythm of the hormonal release. The latter point results in the need
for highly variable hormones (pulsatile) to be
assessed using more frequent specimen sampling
because misleading results can occur if the sampling is too infrequent [118].
Statistical Analysis
The statistical analytical procedures applied to
any research study data are dictated by the design
of that study. Most research in the exercise area
tends to employee parametric analysis (e.g.,
t-test, one-way ANOVA, Pearson correlation).
These analytical procedures work well with
endocrine data, provided that the underlying
assumptions for their use are not violated (see
Ref. [119] for details). Furthermore, many North
American journals prefer this form of analysis
due to the robust nature of the techniques and the
reduced likelihood of making a type I error (indicating findings are significant when they are in
fact, not). Nevertheless, nonparametric analysis
(e.g., Wilcoxon signed-rank test, Mann-Whitney
U test, Friedman test) can be equally applicable
for endocrine use when study designs are not
excessively complex and sample sizes are relatively small [119]. It is important, however, to
recognize the likelihood of increasing the occurrence of a type I error with small sample sizes.
Regardless of whether parametric or nonparametric analyses are used, it is vital that the
researcher report in a publication of their work
what the specific statistical analysis being used is
and what the rationale was for their usage
[118–121].
Once assays are performed and statistical
results are obtained, the researcher needs to try
and understand their data in order to interpret the
magnitude of treatment outcomes and physiological effects. In this interpretative process,
many researchers focus intently only upon
obtaining statistical significance, usually a probability level less than 0.05 (p < 0.05). Obtaining
such significance is important; however, a key
question that has to be addressed in the data is
the issue of “statistical significance” vs. “practical (clinical) significance” for the hormonal findings. To address that question, the researcher
must think about and take into account the smallest clinically important positive and negative
response value levels of the effect being
researched, that is, the smallest change value
levels that matter. Studies can be statistically sig-
1
Methodological Considerations in Exercise Endocrinology
13
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Summary and Conclusion
To conclude, over the last several decades, exercise researchers have steadily increased the number of studies conducted which have examined
the hormones and the endocrine system.
Unfortunately, not all investigators working in
this area of research are entirely aware of the factors that must be accounted for, and controlled, in
order to ensure that valid and accurate data are
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physiological and procedural-analytical factors
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Physiol Endocrinol Metab. 1999;277:E948–57.
121. Matthews DR. Time series analysis in endocrinology. Acta Paediatr Scand Suppl. 1988;347:55–62.
122. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1):1–15.
123. Mohammadreza H, Xu G. A visitor’s guide to effect
sizes—statistical significance versus practical (clinical) importance of research findings. Adv Health Sci
Educ Theory Pract. 2004;9(3):1573–7.
124. Cohen J. Statistical power analysis for the behavioral
sciences. 2nd ed. Englewood: Lawrence Erlbaum;
1988. p. 116–73.
2
Endogenous Opiates and Exercise-­
Related Hypoalgesia
Allan H. Goldfarb, Robert R. Kraemer,
and Brandon A. Baiamonte
Introduction (Endogenous Opiates)
Endogenous opiate-like substances were first
discovered in the mid-1970s, when opioid receptors were identified and located within the brain
and hypothalamus [135]. This led to the discovery that endogenous opioid-like molecules,
enkephalins [69] and endorphins [9, 106], were
produced within the CNS. Subsequently another
class of opiate-like molecules known as dynorphins was identified within the body [14, 50].
The latest addition are nociception/orphanin FQ
molecules which work on nociceptin opioid
receptors (NOP) within the CNS and counteracts
the analgesic effect of opiates. The endogenous
opiates fall into four major classes of substances:
endorphins, a peptide 31 amino acids in length;
enkephalins, smaller peptide molecules that are
five amino acids in length (denoted either as leuor met-, based on the terminal carboxyl amino
acid of the peptide); dynorphins, located in the
A. H. Goldfarb (*)
University of North Carolina Greensboro,
Department of Kinesiology, Greensboro, NC, USA
e-mail: ahgoldfa@uncg.edu
R. R. Kraemer
Southeastern Louisiana University, Department of
Kinesiology and Health Studies, Hammond, LA, USA
e-mail: rkraemer@selu.edu
B. A. Baiamonte
Southeastern Louisiana University, Department
of Psychology, Hammond, LA, USA
e-mail: brandon.baiamonte@selu.edu
posterior lobe of the pituitary gland [86, 107]
and gastrointestinal tract [60] with a 13 amino
acid length; and nociception/orphanin FQ molecules, a peptide of 17 amino acids, which binds
to NOP receptors. Enkephalins were first noted
in areas of the brain and parts of the endocrine
system. The original studies noted that both
endorphins and enkephalins were important regulators of pain [4, 106]. However, more recent
studies have determined that enkephalins not
only play an important role with pain regulation
but affect cardiac function, cellular growth,
immunity, ischemic tolerance, and certain behaviors. Various tissues (heart, smooth and skeletal
muscle, kidney, and intestines) in animals and
humans have recently been shown to have proenkephalin expression [26]. Recently, inflammatory cells were shown to produce and release
these opiates, and endorphins seem to be
involved not only in immune function [79, 81,
123], pain modulation [152], and the exercise
pressor response [72, 125, 162] but also in metabolic control [71, 80, 110, 111, 171]. Therefore,
numerous challenges remain to be clarified concerning the role of these endogenous opiates on
these processes as they relate to exercise. This is
especially true regarding the control of cellular
functions not only under normal conditions but
when acute and chronic exercise stress is
imposed.
Beta-endorphins (βE) were first identified
within specific brain regions and the ­hypothalamus
and were found to bind to mu-opioid receptors
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_2
19
20
A. H. Goldfarb et al.
(MOR). When MOR are activated there is a Peripheral agonists that do not cross the blood
strong inhibition of acute pain [175]. βE within brain barrier can produce analgesia through the
the circulation was first ascribed to βE release DRG [164]. However, research which used
from the anterior pituitary gland after being acti- knockout deletion of mu receptors and DRG
vated by factors within the hypothalamus. These nociceptors in the periphery but with intact CNS
factors activate the anterior pituitary gland to receptors reported these peripheral receptors
synthesize
the
parent
molecule
pro-­were not obligatory for analgesia [23]. It was
opiomelanocortin (PMOC) which can be cleaved suggested that these receptors could be involved
into various active components, one of them with adverse side effects related to tolerance and
being βE. POMC is also expressed in the arcuate opioid-induced hyperalgesia (OIH) with chronic
nucleus as well as the nucleus of the solitary tract agonist treatments. However, brain regions can
within the CNS. βE is therefore an important also contribute to both tolerance and OIH. These
neurotransmitter within the brain and a neurohor- peripheral sensory processes appear to activate
mone outside the CNS when released into the important aspects to initiate or modulate CNS
circulation, to act on mu receptors on target tis- pain circuits [82] and may be activated with exersues throughout the body.
cise [21, 22, 91].
The molecule POMC, the precursor polypepIn addition, there is evidence that serotonin
tide for several factors that arise from the hypo- release which alters behavior is modified by actithalamus and the paraventricular nucleus (PVN) vated opioid receptors to influence γ-aminobutyric
in the brain, can be stimulated by truncated active acid (GABA) involvement [38]. Additionally,
peptides. POMC has a section toward the C ter- interactions have been suggested with MOR with
minus known as β-lipotropin (1–89 amino acids) serotonergic structures involved with both reupthat is ultimately cleaved to β-lipotropin take and release of serotonin [159]. Furthermore,
(1–56 amino acids) and βE (59–89 amino acids). numerous non-opioid analgesics may influence
Both βE and β-lipotropin molecules help to both acute and chronic pain stress [59] and some
mobilize lipid molecules from adipose tissue. are related to cannabinoid action [10, 24, 53, 67,
Originally the assays that were developed to 161]. Therefore, caution should be taken when
measure these molecules did not effectively dif- considering the interpretation of changes which
ferentiate between β-lipotropin and βE, which only measure opioid-like agents without assesswere thus denoted as having both β-lipotropin/βE ing alternative pain influencing agents. There are
activities.
many circuits that can influence pain or its
Neuroanatomical sites for opioid analgesia are attenuation.
present within the CNS and located on neurons
There is limited information related to exerwithin the dorsal root ganglia (DRG) originating cise and brain βE modulation [66, 138, 149]. βE
from peripheral somatosensory DRG neurons immunoactivity in cerebrospinal fluid (CSF) of
that can transmit these activated processes spontaneously hypertensive rats was shown to be
through the spinal cord to the medulla [5]. It significantly higher (about twofold) in runners
should be noted that opioid receptors are (5–6 weeks) than in controls [66]. This study
expressed on these somatosensory neurons pass- also reported that CSF βE was elevated up to
ing through the DRG and have been reported to 48 hours after cessation of voluntary wheel runhave the ability to inhibit or reduce pain percep- ning. It was suggested that this βE effect may be
tion [16]. Both mu and delta opioid receptors are at least partially responsible for the beneficial
located on DRG neurons, and when opioids are effect of exercise on controlling blood pressure
activated, a depressed neuropeptide release from [66]. βE immunoactivity taken from CSF in dogs
these afferents to CNS neurons occurs. Recent was shown to increase with low-intensity exerresearch has suggested that myelinated mechano- cise but not with high-intensity exercise [138].
sensory neurons appear to regulate DRG hyper- In contrast, circulating βE immunoactivity
sensitivity and chronic inflammatory pain [4]. increased in these dogs at both intensities of
2
Endogenous Opiates and Exercise-Related Hypoalgesia
exercise [138]. This indicates that the βE level
within the brain is not reflected by the amount of
βE within the circulation. Rat brain receptor
binding of [3H]diprenorphine, a βE analog, was
not significantly elevated 1 hour following a
swim but was increased in several brain regions
(5 of 6) 2 hours after exercise [149]. It is unclear
if this was related to changes in βE concentration
or a change in receptor availability. Pain threshold increase that occurred with exercise was
abolished when naloxone (a receptor antagonist
for βE) was injected into brain ventricles after
5 weeks of exercise training [155]. This suggests
that the opioids were involved in elevating pain
threshold in response to exercise training in
these rats. Clearly more work is needed in this
area. Specific brain areas that might be involved
with BE and pain regulation in response to different types of exercise still needs further
investigation.
βE within the circulation has been implicated
in a number of processes including immune function, pain modulation, and assisting in glucose
and lipid homeostasis. The major function of
these endogenous opiate-like molecules was first
identified as modulators of pain and euphoria
based on the receptors they activated. As a result
of this, the phenomena known as “runner’s high,”
“second wind,” and “exercise dependency” were
postulated to be related to this endogenous
activity.
This chapter will summarize what is currently
known about the stimulation of these endogenous
opiates in response to exercise or physical activity, and how exercise may induce exercise-­
induced hypoalgesia (EIH). The influence of an
acute bout of exercise on the βE response will be
presented first as these studies were the impetus
of the original research. The influence of training
on βE will then be discussed. Then the influence
of an acute bout of exercise on enkephalins will
be presented followed by training influences on
enkephalins. The physiological mechanisms
responsible for activation and secretion of these
substances will be briefly discussed when known
and related to functional outcomes when possible. Finally the effects of EIH will then be
presented.
21
I nfluence of Acute Exercise
on β-Endorphin Levels
The initial studies that were conducted to examine the impact of exercise on endogenous βE levels utilized various modes of exercise. The
original articles examined various activities such
as running at various distances to determine if
blood βE level was elevated [15, 21, 25, 170].
These studies noted elevated βE after the exercise
activities which led to more controlled experiments utilizing incremental graded exercise tests
in laboratories to ascertain the βE response [48,
61, 62, 120, 130, 139]. These studies suggested
that blood βE can increase from 1.5- to 7-fold following these graded exercise tests. The large
variation in the βE response was in part attributed
to procedural methods for the exercise tests as
well as methods to determine βE and possibly
related to the subjects utilized.
erobic Exercise at Work Intensities
A
Related to Percentage of VO2 Max
on β-Endorphin
Several studies determined whether there was an
exercise intensity effect on blood βE level.
McMurray et al. [118] was one of the first
researchers to examine the βE response to a specific exercise intensity. Donevan and Andrew
[28] noted that βE did not increase after 8 minutes of cycling at 25% and 50% maximal oxygen
uptake (VO2 max) but increased after 75% VO2
max after similar duration. They also reported a
greater increase in βE at 95% VO2 max. Goldfarb
et al., in that same year, examined the effects of
cycling at several intensities of exercise (60%,
70%, and 80% VO2 max) to determine if there
was a critical exercise intensity needed to induce
circulating βE [46]. βE concentration increased
in the two higher exercise intensities but not at
60% VO2 max. The time course of βE changes at
these exercise intensities up to 30 minutes of
exercise was examined with βE increases occurring earlier with the highest exercise intensity (by
5 minutes). Research comparing 60% VO2 max
and 80% VO2 max as well as self-paced running
22
for 30 minutes noted only an increase after the
80% run [33]; however, they utilized βE/Blipotropin immunoreactivity. A run at 60% VO2
max for 60 minutes induced no change in βE
[103]. Exercise at 80% VO2 max for 30 minutes
with or without naloxone increased βE with a
greater augmented increase with naloxone [1].
These studies taken together suggested that circulating βE increases with an appropriate minimal exercise intensity (>60% VO2 max), but this
was not always the case. The time course information also suggested that higher intensities of
exercise would result in βE increases more rapidly [33, 35, 49, 61]. Later it was reported that
gender did not influence the βE response to either
60% or 80% VO2 max [32, 61, 65, 140].
It was noted that menstrual cycle had minimal
effects on the exercise βE response in women
[45, 49]. However, other factors might have differed which could have contributed to the discrepancy in the literature such as nutritional
status of the individuals, time of day, immune
function, and training status. Farrell et al. noted
that βE+/β-lipotropin levels in well-trained
endurance athletes only increased at 92% VO2
max whereas lower intensities did not elicit significant increases [33].
Instead of a critical intensity relative to one’s
maximal aerobic capacity, other studies related the
increase in circulating βE to lactate threshold [148].
They plotted the change in lactate with increased
work intensity and compared the βE response.
Incremental increases in exercise intensity elevated
circulating βE levels and showed a similar pattern
of change as blood lactate. However, it should be
noted that these similar changes are only for shortduration incremental exercise. For activities with
longer duration, the βE increase does not coincide
with lactate changes [46]. In addition, other factors
such as diet, training status, and immune function
can influence the βE response.
High-Intensity Bouts
with an Anaerobic Component
Short bouts of highly intensive exercise (anaerobic exercise), consisting of various types of exercise from a few seconds up to several minutes
A. H. Goldfarb et al.
duration, can induce an increase of βE. A few
studies reported that βE concentration in the circulation can increase about 2–4-fold above resting with these high-intensity anaerobic exercise
bouts [35, 120, 139, 148]. Schwarz et al. noted a
significant increase in blood catecholamines that
correlated with the maximal lactate concentrations in response to exercise. Stimulation of the
HPA axis through sympathetic activation appears
to be related to the release of βE into the
circulation.
Investigations of resistance exercise as a stimulus to augment circulating βE concentration in
humans includes a limited number of published
studies. Equivocal results have been reported,
and this may be related to differences in subjects,
type of exercise intensity, workload volume, and
time of measurement. Typically the resistance
exercise was related to the person’s 1-repetition
maximum (1-RM), i.e., maximum weight that
was lifted or pushed/pulled by a subject with
maximal effort. Often the load is referenced as a
percentage of the 1-RM. Circulating βE level
increased in response to high total workloads
[97]. These authors suggested that the total work,
rest to work ratio, and total force needed most
likely influenced the βE response. An increase in
βE in 28 elite male weight lifters was demonstrated after a moderate- to high-intensity workload [98]. An increase in βE level also occurred
after three sets of work at 85% 1-RM in females
but was significantly elevated (3.7-fold) only
when these women were in a negative energy balance [172]. An increased βE/β lipotropin level
was reported in response to weight lifting in five
males [31].
In contrast, Kraemer et al. conducted a study
using low-volume resistance exercise as a stimulus and reported no change in βE levels [95].
Furthermore, blood βE level based on immunoreactivity decreased after exercise compared to
at rest in ten male and ten female college-aged
­students who performed three sets of eight repetitions at 80% 1-RM on four exercises [136].
This same group had reported earlier that
resistance-­trained subjects (N = 6) showed no
change in blood βE level compared to baseline
after three sets of eight repetitions at 80% 1-RM
[137]. Both resistance exercise and treadmill
2
Endogenous Opiates and Exercise-Related Hypoalgesia
exercise were reported to significantly increase
circulating βE/B-lipotropin immunoreactivity
[31]. Unfortunately the intensity and volume of
exercise was not available. McGowan et al.,
however, noted a decrease in βE concentration
after exercise at 80% 1-RM in 20 college-aged
subjects (both genders) [117]. It appears that
resistance exercise of sufficient intensity and
volume (workload) can result in a transient βE
increases within the circulation in both men and
women, but this finding is sometimes equivocal.
Influence of Training
on β-Endorphin Levels
The training status of the individual can influence
the response to exercise for a number of reasons.
One reason is related to the relative intensity of
the exercise. Well-trained athletes can typically
perform at a greater absolute workload and usually would exercise at a higher relative workload
compared to an untrained individual. Therefore,
when comparing the βE response one should
compare the absolute workload and the relative
intensity. In addition, other factors might influence the secretion of βE such as the diet or
immune function which can be influenced by
training. Typically one would expect a downregulation on the secretion of βE to a similar absolute workload. However, there could be an
upregulation of the capacity of the hypothalamic–pituitary–adrenal (HPA) axis in trained
individuals. Finally, the amount of free hormone
and the number of binding receptors could be
modulated to influence action on target tissues.
Influence of Endurance Training
Resting levels of βE in endurance-trained individuals were reported to be lower [66] with the
vast amount of studies reporting no change [45,
61, 62, 68]. The studies that reported no changes
were mostly cross-sectional studies. In contrast,
the study that reported lower levels used an
endurance training program and compared the
βE level before and after the training program at
rest [109]. In contrast, Heitkamp reported that
23
women who trained three times per week for
30 minutes each time at their individualized lactate threshold did not have changes in their resting βE [61]. Harber and associates compared
normal eumenorrheic sedentary to eumenorrheic-trained and amenorrheic-­
trained women
and reported that βE varied considerably, but
there was no menstrual cycle effect at rest on βE
[56]. They also noted that resting βE levels were
higher in the trained women compared to the
sedentary women. Goldfarb et al. reported a
trend for lower βE levels during the luteal phase
of the menstrual cycle compared with the follicular phase, but this did not reach significance
[49]. They also noted no significant difference in
βE at rest between men and women. Therefore,
there is currently no consensus in the literature
as to the effect of endurance training on resting
βE levels.
The βE response during exercise is in slightly
better agreement when exercise intensities were
controlled. One early study reported a higher βE
concentration after 4 months of aerobic training
six times per week [15]. They reported that the
βE level was higher cycling at 85% max heart
rate (HR) than before training. This occurred
after 2 months of training with no further changes.
It should be noted, however, that to elicit a similar 85% max HR, the subjects worked at a greater
absolute workload.
Most of the other studies have reported no
detectable differences in trained and untrained
subjects regardless of whether it was a cross-­
sectional design [47] or longitudinal design [12,
32, 61, 62, 68]. Goldfarb et al. compared
untrained (N = 6) and trained cyclists (N = 6) that
cycled for 30 minutes at 60%, 70%, and 80% VO2
max with subjects randomly assigned in a
­counterbalanced order [47]. There was no difference in the βE concentration for the trained and
untrained at similar relative workloads despite
higher absolute workloads for the trained group.
Both untrained and trained groups responded
with higher βE levels at both 70% and 80% workloads compared to rest and the 60% workload.
Heitkamp et al. reported that after training the βE
response was comparable but was obtained at
higher absolute workload for the trained subjects
[61]. They also reported that after training the
24
recovery βE was lower suggesting faster removal
of βE. Howlett et al. also reported no difference
in βE concentration after endurance training at
maximal workloads but met-enkephalin concentration was reduced after 4 months of training
[68]. Bullen et al. reported greater peak βE/β-­lipotropin post-exercise after 8 weeks of cycling
training in seven women [12]. Engfred reported
similar βE increases after 5 weeks of cycling
training at 70% VO2 max cycling to exhaustion
[32]. VO2 max increased 12% following 5 weeks
of training so a higher absolute workload after
training was utilized. In conclusion, it appears
that blood βE concentration in trained individuals
will be similar to concentrations before training
if the workload is at the same relative intensity of
aerobic capacity. This would require a higher
absolute workload for the trained individual.
A. H. Goldfarb et al.
pose tissue, pancreas, and skeletal muscle.
However, the exact role(s) βE may have on these
tissues is still being elucidated.
The influence of βE on immune function has
been investigated in vitro but has not been adequately investigated in vivo. βE in rats and
humans was shown to stimulate T lymphocyte
proliferation [63]. The data suggests that βE
mode of action was not though a MOR. It was
shown that synthetic βE could bind to non-opioid receptors on T lymphocytes, and this binding was not blocked by naloxone or
met-enkephalin [126].
In vitro βE stimulated rat spleen lymphocytes
in a dose-dependent manner by enhancing the
proliferative response to several mitogens [44].
This binding was not blocked by naloxone. βE
enhanced the proliferative response of splenocytes on T-cells from adult male F344 rats [165].
In addition, naloxone was not effective in blocking the βE effect. βE stimulated the proliferative
Influence of Resistance Training
effect on human T lymphocytes using the mitoon Circulating β-Endorphin
gen concanavalin A [131]. This βE-stimulated
Unfortunately there are few studies that have mitogen response demonstrated a bell-shaped
examined the influence of resistance training on curve indicating that too high a dose would actucirculating βE. There are no published studies ally inhibit the response. It was suggested that
found which indicate that βE concentration this response may change with time, dose, or
would change at rest or at any specific workload mitogen used [121]. These authors also reported
or a percentage (%) of one’s maximal capacity that the inhibition of the immune response to
maybe
partially
reversed
by
with resistance training. Fry and coworkers cortisol
reported similar βE concentration after both 4 βE. Therefore, the activation of βE may inhibit
and 9 weeks of resistance training to baseline lev- suppression of the immune response by acting
els [40]. It is important to note that most of the on cortisol actions in vivo.
The βE effect on to enhance natural killer
resistance research typically utilized resistance-­
trained subjects. As noted above, higher total (NK) cell function in vitro was reported to be a
work volume with resistance exercise resulted in dose-dependent manner but was inhibited by
naloxone [85]. This suggests that the mode of
greater increases in circulating βE [97].
action on NK cells appears to be different than
the enhancement of T lymphocyte function. The
effect of βE concentration on NK cell activity
β-Endorphin and the Immune
(NKCA) and amount was examined after exerSystem
cise [43]. Naltrexone treatment administered
βE within the circulation has been implicated in a 60 minutes before a run at 65% VO2 max which
number of processes including modulation of elevated blood βE levels at 90 and 120 minutes
immune function, pain modulation, blood pres- did not alter the exercise response in NKCA or
sure regulation, and assisting in glucose homeo- amount. These authors suggested that βE may
stasis. βE receptors have been identified in many work independent of the MOR action to assist
locations within the body including nerves, adi- NKCA [79]. Chronic exercise (wheel running
2
Endogenous Opiates and Exercise-Related Hypoalgesia
for 5 weeks) in spontaneously hypertensive rats
enhanced NKCA. The βE levels in CSF
increased after the running and enhanced lymphoma cell clearance from the lungs. The deltareceptor antagonist naltrindole significantly but
not completely inhibited the enhanced NKCA
after 5 weeks of exercise. Neither α nor β receptor antagonists influenced the NKCA. These
authors suggested that the endurance training
mediated central receptor-mediated adaptations.
However, if βE levels increased in the periphery
via subcutaneous administration, this did not
alter NKCA in vivo [79]. In contrast, NKCA
after central injection of a delta opioid receptor
agonist was depressed [3]. In addition, a single
injection of a mu agonist into the intracerebral
ventricle reduced NKCA activity. Furthermore,
a single morphine injection into the periaqueductal area suppressed NKCA [173]. These
findings suggest that central-mediated βE levels
may act to modulate NKCA via both delta and
mu receptors. Clearly more research with human
models is needed, but this may be difficult as
most of these actions appear to be centrally
mediated.
Additional βE modes of action on the immune
response include mononuclear cell chemotaxis
[133, 166], immunoglobulin migration [146,
166], and lymphokine production [166].
Macrophages showed migration to βE levels
injected into the cerebral ventricles in rats [166].
Human neutrophils demonstrated enhanced
migration to β receptors when βE was infused,
and this response was blocked by prior incubation with naloxone. Analogs of opioids appear to
have different responses when injected into the
cerebral ventricles [146]. Some may stimulate
macrophages, and others may influence neutrophils. The chemotaxis response appears to be
dose-dependent [133]. High doses of βE (10−3 M)
inhibited the chemotaxis response whereas low
concentrations stimulated upregulation of neutrophils. Since physiological βE concentration is
below the high-dose level utilized even when
elevated by exercise or other stressors, it is likely
that βE at these low levels provides a stimulatory
effect on this aspect of the immune system. It was
also noted that endogenous opioids which may
25
be elevated with exercise training induce a secondary antibody response in mice [83].
It was postulated that the opioid peptides such
as βE and the enkephalins have a similar structural component to that of interleukin-2 [76].
Interleukin-2 and other interleukins are involved
in the inflammatory response and are targets of
βE levels and cortisol. It is highly likely that both
βE levels and cortisol influence immune
responses by interacting with interleukins [174].
The inhibitory response may act at a number of
levels including the attenuation of production of
both interleukin-1 and interleukin-6 in a dose-­
dependent manner.
It appears that βE may act on a number of
immune factors both centrally and peripherally
and may act through both opioid and non-opioid
receptors. Additionally, βE action may work
through direct inhibition of cortisol. Both βE and
cortisol influence immune function with βE generally enhancing immune function and cortisol
acting as an immunosuppressant. The interplay
of βE and cortisol in regulating immune function
in response to both acute and chronic exercise
requires more research to clarify their contributions. Training adaptation effects also need further study. In addition, nutritional factors (i.e.,
carbohydrate level) have not been adequately
examined in relation to both βE and cortisol
influence on immune responses with exercise. It
was reported that βE increased to a similar level
after cycling to exhaustion (90% VO2 max after
cycling for 60 minutes at 65% VO2 max) independent of a high or a low glycemic diet or placebo prior to the exercise [72]. More studies are
needed to clarify the role of diet on the βE
response to exercise.
ndogenous Opioids and Pain
E
Perception
There are numerous citations that have implicated endogenous opioids and pain perception. A
good number of these have suggested that endogenous opioids are involved in the processes of
myocardial ischemia and or angina [74, 156]. It
was reported that endorphins could modulate
26
adenosine-provoked angina pectoris-like pain in
a dose-dependent manner in seven healthy subjects [156]. In contrast, met-enkephalin had no
apparent effect on the pain. There may be a gender difference as angina pectoris pain induced by
adenosine was attenuated by βE in males (both
healthy and with coronary artery disease), but βE
infusion did not modulate the pain nor did naloxone in females [144]. Increased plasma concentrations of βE were shown to alter peripheral pain
threshold but did not alter angina threshold in
patients with stable angina pectoris [74].
Therefore, peripheral pain may be influenced by
βE, and the βE level may in part manifest some
alteration in pain threshold. However, it is more
likely that peripheral nerves which contain βE
and/or immunocytes which release βE are
involved with altering pain perception and reduction of damage [124].
Several studies have reported that exercise can
modulate pain perception, and this has been
attributed to endogenous opioids. Both acute and
chronic exercise was reported to significantly
enhance MOR expression in the hippocampal
formation [27]. However, acute and chronic exercise had no significant effect on MOR expression
in trained rats. Immunohistochemical techniques
showed a higher number of MOR-positive cells
after acute exercise compared to a control group.
These authors noted that both acute and chronic
exercise modulate MOR expression in the hippocampus region of rats. Higher pain thresholds for
pain were reported in individuals who exercised
for both finger and dental pulp stimulations [29].
Plasma βE levels increased after exercise to
exhaustion as did cortisol and catecholamines,
but pain threshold level changes did not correlate
with plasma βE. Furthermore, naloxone failed to
affect pain thresholds, despite the fact that with
naloxone and exercise, βE levels increased to a
greater extent. These authors suggested that the
pain-related changes with exercise were not
directly related to plasma βE. Janal et al. reported
that after a 6.3 mile run at 85% VO2 max, hypoanalgesic effects to thermal, ischemic, and cold-­
pressor pain occurred, together with elevated
mood [73]. In this study, naloxone infusion partially inhibited some of the pain and mood effects
A. H. Goldfarb et al.
with the exercise. This suggests that exercise can
modulate pain, and it appears it is related to βE
but may not be related to the plasma βE
concentration.
Perception of pain in trained men (N = 17)
after a run (12 minute for maximal distance) with
either placebo or with naloxone was examined
[134]. Post-exercise βE levels increased to a similar extent for both trials, but pain level was
greater with the naloxone treatment. These
authors concluded that the perception of pain
associated with exhaustive exercise may be
related to endogenous opiates, but this had no
effect on performance. Low-intensity exercise
reversed muscle pain in rats, and this was blocked
by naloxone [6]. Microinjections of opiates into
the periaqueductal gray matter in the brain of rats
attenuated pain symptoms [152]. It was found
that systemic and supraspinal opiates could suppress pain in rats [106]. These studies clearly
suggest that pain can be altered by opiates and
that exercise can modify pain; however, the alteration in pain does not appear to be related to circulating βE.
Neuropathy-induced mechanical hypersensitivity occurred in wild-type mice subjected to a
chronic constriction injury of the sciatic nerve
[102]. It was reported that T lymphocytes infiltrating the injury site (11% of total immune cells)
released βE. Corticotropin-releasing factor (CRF)
was applied at the injured nerve site and fully
reversed the hypersensitivity. These authors suggested that the T lymphocytes which contain βE
are crucial for not only immune function but also
altered pain with peripheral nerves.
It is now clear that βE is found in parts of the
immune system and can act both centrally and
peripherally to help modulate pain. It is unclear
how these different areas in the body respond to
both acute and chronic exercise, but it appears
that βE are involved. Part of the modulation of
pain perception is clearly related to MOR
within the brain, and more research is needed to
understand the effects of both acute and chronic
exercise on these receptors. In addition, circulating βE may increase, but this may not always
be related to pain modification, and naloxone
may not always block this effect. Therefore, the
2
Endogenous Opiates and Exercise-Related Hypoalgesia
peripheral-mediated βE effect on pain thresholds may not be related to the MOR in the
periphery.
β-Endorphin and Glucoregulation
The opioid system has been implicated in the
control of blood glucose concentration during
rest [36, 142] and exercise [37, 71, 72]. βE and
opiate receptors have been isolated from sites
that are involved in glucoregulation [173].
Additionally, it has been reported that βE appears
to play a role in metabolic regulation during exercise or muscle contraction [132, 137]. A bolus
injection of βE followed by intravenous infusion
of βE in rats raised βE levels 6–7-fold and
resulted in higher plasma glucose levels at 60 and
90 minutes of exercise compared to saline infusion [37]. Lower insulin and higher glucagon levels were evident compared to saline infused rats
at these times. Additionally βE exerts an effect on
insulin and glucagon at rest [36, 132] in humans
and animals. βE infusion without a bolus infusion
of βE compared to saline infusion enhanced glucose homeostasis and exacerbated the glucagon
rise in rats that were exercised [71]. This study
reported that βE infusion independent of a βE
bolus during exercise can attenuate blood glucose
decline and increase glucagon levels in response
to exercise. Additionally, βE infusion alone did
not alter insulin, catecholamines, corticosterone,
or FFA’s response during exercise. It appears that
βE infusion alone at a level to increase circulating
βE at 2.5-fold greater than normal level does not
inhibit insulin; however, if the βE level increased
to greater than 2.5-fold (infusion and/or increase
by exercise), inhibition of insulin occurred possibly related to help maintain blood glucose.
I nfluence of Acute Exercise
on Enkephalins
There is some evidence that exercise can increase
enkephalin concentration and or opioid receptor
numbers in the brain [18, 27]. These alterations
in the brain have been linked to changes in mood
27
state [46], control of exercise blood pressure [7,
70, 75, 125], cardiac ischemia and angina [156],
pain [154, 156], and immune function [13].
However, some of the actions of these opioid
molecules may manifest themselves in other
compartments such as vascular control. Research
is unfolding regarding the actions of these
enkephalins and enkephalin-like molecules. For
example, proenkephalin peptide F which is primarily released from the adrenal gland and
co-­released with epinephrine has immune-modulating functions [13, 81, 160].
Met-enkephalin level was unchanged after a
Nordic ski race determined in both highly trained
(N = 11, 150 km/week with greater than 3 years
of experience) or recreationally trained (N = 6,
20 km/week with no competitive experience) skiers [122]. The distance covered was 75.7 km, and
subjects were allowed to have water and food ad
libitum. Met-enkephalin plasma concentration
was determined at rest prior to a graded treadmill
exercise to exhaustion and after a run of 87.2 km
(5 minutes post exercise). The basal level of
enkephalin was 171.7 ± 7.16 fmol/mL and
increased after the treadmill exercise to
265.8 ± 9.88 fmol/mL with a further increase
after the run to 378.3 ± 15.16 fmol/mL. The
authors suggested that the increase in met-­
enkephalin in plasma may be related to intensity
and duration of exercise [153]. The same authors
compared unfit (N = 24) and fit (N = 23) subjects
exposed to a graded intensity treadmill run to
exhaustion (4 minute stages of at least five
stages). Plasma Met-enkephalin concentration
was lower for the unfit compared to the fit
(126.3 ± 5.3 fmol/mL vs. 156.7 ± 6.9 fmol/mL).
Both groups demonstrated increased plasma met-­
enkephalin after the exercise with the fit group
showing a greater response (unfit = 180.4 ± 5.3
fmol/mL vs. fit = 278 ± 6.58 fmol/mL) [154]. In
contrast, Boone et al. reported that ­met-­enkephalin
was no different in trained and untrained subjects
following 4 minutes of exercise at 70% VO2 max
and 2 minutes at 120% VO2 max [8]. These
authors noted that cryptic met-­enkephalin (activated) was elevated similarly in both groups after
the 70% VO2 max and returned to baseline levels
at the higher workload.
28
The response to exercise in met-enkephalin
concentration in the plasma from trained and
untrained subjects was reported to be similar
[75]. Subjects rested for at least 15 minutes prior
to collection of a resting blood sample and then
performed a graded treadmill protocol to maximum, after which another blood sample was
attained. There was no difference in the met-­
enkephalin concentration in plasma, red cells,
cytoplasm, or ghosts when comparing pre- to
post-exercise in both trained and untrained
groups. However, the degradation rate was slower
in the trained group compared to the untrained
group independent of time (pre- and post-­
exercise). The authors suggested this may facilitate opioid responses and could provide tolerance
for trained subjects.
One of the early investigations in this area
examined leu-enkephalin activity in plasma both
before and after a competitive run [34]. Blood
samples were obtained from experience runners
(9 males; 5 females) before and after a 10 mile
road race (2–8 minutes). Resting leu-enkephalin
was 22.2 ± 13.7 pmol/mL and increased
(p > 0.05) to 26.1 ± 21.5 pmol/mL, a modest
increase. The leu-enkephalin change was inconsistent and variable among the runners.
In conclusion, the influence of exercise on
met-enkephalin is variable and appears to depend
on assay method. There is inconsistency in the
results, as some studies suggest enhanced levels
and others no change. There is insufficient data to
suggest that aerobic capacity or fitness level
alters met-enkephalin level. Additionally, leu-­
enkephalin research suggests a modest increase
in blood concentration with large individual variation responses with limited research.
There is limited information on exercise training programs with enkephalins. Chen et al. examined acute and chronic exercise training effects
on leu-enkephalin in the caudate-putamen of rat
brains and compared the levels to sedentary control rats [18]. The trained rats exercised for
5 weeks on a motorized treadmill with a progressive overload in time and speed and ran 5–7 days
per week. Staining of leu-enkephalin was primarily in the PVN and the caudate-putamen region
(CPR). Acute exercise increased staining in the
A. H. Goldfarb et al.
CPR region and remained elevated in this region
for up to 180 minutes post-exercise with a gradual decrease over time [18]. These results suggest
that there is a central-mediated enkephalin
response influencing the brain to the acute exercise in these brain regions. It also suggests that
this response is transitory and reverts back to normal over time. Unfortunately, this study did not
include a sedentary acute exercise group to determine whether the endurance training elicited different results than an acute exercise bout.
There is also limited information with regard
to the influence of exercise on proenkephalin
peptide F that is typically released from the adrenal medulla and co-released with epinephrine
[108]. The influence of exercise intensity and
training was examined in college-aged students
[100]. The trained subjects were middle-distance
runners (N = 10) and were compared to untrained
individuals (N = 10). The subjects exercised on a
cycle ergometer for 8 minutes stages that elicited
28%, 54%, and 84% VO2 max and then exercised
to VO2 max. Peptide F levels at rest were twice as
high in the trained group compared to untrained
but were very low (<0.1 pmol/mL). Neither group
demonstrated any change in peptide F at the lowest workload, but there was a significant increase
at 54% workload in the trained group. Peptide F
stayed at a fairly constant concentration at the
higher work intensities (~0.4 pmol/mL). In contrast, the untrained group demonstrated an
increase in peptide F at 100% VO2 max that was
similar to the level of the trained group. It is interesting to note that the epinephrine level for both
groups showed a similar response. This suggests
that peptide F level may be related to other factors than its release and epinephrine level.
The effect of fitness and intensity of exercise
was examined in women to see if peptide F levels
might be altered differently in women [160].
Women who were endurance trained (>3 times
per week, 30–45 minutes/session) were compared to inactive women. They were tested on a
cycle ergometer at 60% and 80% VO2 max
(15 minutes at each workload) during the early
follicular phase of the menstrual cycle. Blood
was collected at rest and 10 minutes into each
intensity. Only the fit women demonstrated a sig-
2
Endogenous Opiates and Exercise-Related Hypoalgesia
nificant increase in peptide F at the 80% intensity
workload. However, this increase was modest
(0.046–0.056 pmol/mL). In contrast, untrained
women showed a greater epinephrine level compared to the fit women. This again suggests dissociation in the amount of epinephrine and
peptide F within the circulation.
The menstrual cycle effect on peptide F to
maximal exercise was reported in eumenorrheic
women (N = 8) [99]. There appeared to be a slight
but insignificant (0.06) effect of menstrual cycle
on plasma peptide F level at rest. In addition,
there was no exercise main effect on plasma peptide F levels. These results suggest there may be
fluctuations in peptide F levels over time as well
as over the course of the menstrual cycle. This
also suggests that the changes in the previous
study with lower peptide F levels may be an
anomaly. Clearly, more research studies with
exercise on peptide F levels. Furthermore, many
of the variables that might influence baseline
peptide F levels should be considered.
Exercise-Induced Hypoalgesia
Physical activity is known to be critical for health,
longevity, and high quality of life [129] and is an
effective treatment as well as prevention of certain diseases [19, 77, 110, 145]. Chronic exercise
has been shown to increase coordination and
aerobic fitness, decrease risk of various cardiovascular diseases [112, 150], and enhance body
image, self-efficacy, and emotional stability
while alleviating depression and reducing anxiety and stress [54]. In addition, research has also
indicated health benefits associated with acute
exercise. Some forms of acute exercise influence
pain perception by decreasing pain sensitivity in
healthy individuals following a bout of exercise
[88, 128]. This decrease in pain sensitivity, which
is known as exercise-induced hypoalgesia (EIH),
occurs during and after higher intensities and
longer periods of aerobic exercise [66, 89].
Recent evidence suggests that signaling molecules carried in the circulation or through nerves
are important for exercise-induced hypoalgesia.
Jones et al. measured pressure pain thresholds in
29
subjects 5 minutes after high-intensity cycling
with one arm occluded and the other with normal
blood flow [78]. The investigators reported that a
reduced EIH effect occurred in the occluded arm.
This analgesic phenomenon is of great interest as
exercise regimens are becoming the focal point
of most pain management programs [141]. A
review of the literature on EIH reveals that
healthy individuals will demonstrate hypoalgesia
following most modalities of exercise including
aerobic, isometric, and dynamic resistance exercise [2, 124]. However, there are differences in
the degree to which each modality alters pain
perception. According to the results from a meta-­
analysis, aerobic exercise produces EIH in
response to both pressure and thermal pain stimuli and seemed to be the strongest when performed at moderate-to-high intensity [124].
Isometric exercise produced the largest effect
size of the modalities, and this was consistent
regardless of pain stimulus and exercise intensity.
There is a paucity of findings [2, 39, 90] on
dynamic resistance exercise, and the effect sizes
were large when pain was assessed immediately
after exercise. While these studies have provided
great insight into the effects of dynamic resistance exercise on EIH, there are a few key aspects
of these studies that should be addressed to elucidate the effects of dynamic resistance exercise on
pain perception. The first important discrepancy
in research methodology is the inconsistencies in
time points in which pain was assessed after exercise. Koltyn and Arbogast [90] measured pain
perception at 5 and 15 minutes post-exercise,
whereas Focht and Koltyn [39] assessed pain at 1
and 15 minutes time points, and Baiamonte et al.
[2] utilized all three time points (1, 5, and 15 minutes post exercise). In addition, the exercise protocol implemented in each study varied in terms
of sets, repetitions, intensity, and duration.
Baiamonte et al. utilized 9 lifts and participants
were required to perform three sets of 12 repetitions at 60% 1-RM for 45 minutes with a 1:1
work to rest ratio, while the previous two studies
consisted of only four movements of three sets of
10 repetitions at 75% 1-RM for 45 minutes where
the work to rest ratio was unclear but appears to
be longer rest [2]. The structure of the resistance
30
A. H. Goldfarb et al.
exercise protocol probably influences pain per- beta-endorphin and encephalin [55]. There is eviception and the mechanisms responsible for dence that patients with chronic low back pain
EIH. In summary, all three modalities of exercise have greater activity in pain-related areas of the
produced moderate-to-large effects in healthy brain, whereas there is reduced activity in analgeindividuals depending on the protocol. The EIH sic regions of the brain [101]. Recent evidence
effects were transient with optimal resistance for fibromyalgia patients suggests that after ten
exercise dose along with mechanisms responsi- treatments of transcranial direct current stimulable for this phenomenon still unclear.
tion, pain was reduced, mood was improved, and
Aerobic exercise and resistance exercise are these changes were related to circulating concenknown to elicit EIH for a brief period [2, 124]. trations of beta-endorphin [87].
Since aerobic exercise [46, 47, 48] and resistance
Chronic pain disorders such as lower back
exercise [56] of high enough intensity [46, 95, pain [167] and fibromyalgia [11, 114] are often
96] are known to enhance circulating endogenous treated with exercise therapy [127]. Patients with
opioids, it has been speculated that EIH is due to low back pain have significant pain reduction folpain modulating substances such as beta-­ lowing treatments of aquatic exercise [151], and
endorphin [88, 90, 118, 127]; however, this has unsupervised, low volume trunk exercises have
not been fully supported. While the EIH findings also been shown to reduce pain in these individuhave been consistent for these exercise modali- als [57]; however, patients with long-term whipties at higher intensities in healthy participants, lash disorder do not show reductions in long-term
the evidence supporting the effectiveness of exer- pain after exercise treatments [52].
cise on chronic pain patients is limited. The EIH
Research has indicated that stimulation of
findings in healthy individuals are more consis- afferent A-delta and C fibers via muscle contractent when compared to EIH in chronic pain popu- tions during exercise will activate spinal and
lations, which produced variable outcomes with supraspinal inhibitory signaling to dampen pain
small-to-large effects in individuals with regional perception [91, 158]. Both animal and human
chronic pain conditions [124]. This variability studies have verified this mechanism, but findcould be explained by the exercise intensity, loca- ings have been controversial. Most studies have
tion of chronic pain condition in relation to utilized administration of opioid antagonists (nalexperimental pain induction site, and severity of trexone or naloxone) prior to exercise which
chronic pain condition. Interestingly, there was should bind to the mu-opioid receptors and theono evidence of EIH in patients with widespread retically prevent or reduce EIH. In both human
chronic pain conditions and at times, exercise at and animal studies, the results were mixed with
moderate-to-high intensity exacerbated the pain. attenuation of EIH with opioid antagonist prior to
Moreover, it has been suggested that greater sen- exercise in some studies and insensitivity to opisitivity to pain in response to pressure in muscle oid antagonist in another [88]. Researchers have
after static contractions in patients with fibromy- suggested that the equivocal findings are due in
algia [92, 93, 129] suggests that patients with part to methodological differences which resulted
fibromyalgia possibly have dysfunction of endog- in different exercise intensity, duration, and varienous analgesia during exercise compared with ations in opioid antagonist administration [91].
reduced pain sensitivity in healthy patients dur- In fact, previous research has revealed that
ing exercise [94]. However, an acute exercise ses- manipulation of the exercise protocol in animal
sion by women with chronic neck pain was research produce differences in EIH following
shown to reduce pain intensity and sensitivity opioid antagonist administration [22]. Therefore,
which was associated with greater circulating animal research has indicated that there may be
beta-endorphin and cortisol concentrations [84]. multiple mechanisms (both opioid and non-­
Electroacupuncture has been used to treat opioid systems) involved in EIH [67, 91].
chronic pain and studies have reported that elec- Researchers have suggested involvement of the
troacupuncture at 2 Hz will enhance release of endocannabinoid system in EIH due to the
2
Endogenous Opiates and Exercise-Related Hypoalgesia
presence of CB1 receptors in pain processing
areas [53, 64, 161] and evidence of increased
endocannabinoid concentration after exercise
[24, 41–43, 91]. A recent study by Crombie et al.
[24] demonstrated an interaction between opioid
system and endocannabinoid system. When participants were administered naltrexone, the endocannabinoid 2-arachidonoylglycerol (2-AG)
increased significantly following exercise.
Even more interesting, the endocannabinoid
N-arachidonoylethanolamine (AEA) did not
increase following administration of naltrexone
and exercise. Therefore, increases in AEA typically observed after exercise were blocked by
administration of an opioid antagonist, which
suggests an interaction between the two systems.
The recent work with MOR inhibition resulting
in decreased voluntary wheel running in rats suggests this signaling in a dopamine-dependent
manner supports complex regulation of pain at
multiple levels within the brain [143]. This study
noted that an overlap may at least partially
explain why some individuals sense pleasure
with exercise and others may not. Future research
should focus on the complex interplay between
the opioid and non-opioid systems on EIH rather
than concentrating on each system independently.
Investigation into the interaction between these
two systems and probably other pathways should
provide further evidence of the multiple mechanisms involved in EIH. This should provide
insights into more appropriate treatments for prescribing dose and exercise intensity needed to
take advantage of all the physical and mental
benefits that exercise has to offer besides just
EIH.
-Endorphin and Pain in Clinical
β
Populations
There are a number of studies that investigated
the effects of exercise on βE in different clinical
populations affected by pain. Circulating concentrations of several neuropeptides, steroid hormones and metabolites were assessed after
exercise to determine if women with chronic
neck/shoulder pain responded differently than
31
healthy women [84]. The investigators used
microdialysis to analyze substance P, βE, cortisol, glutamate, lactate, and pyruvate before and
after an exercise training regimen. They also
assessed pain intensity and pain threshold. Before
the training regimen, women with neck/shoulder
pain had higher circulating levels of glutamate
and βE and lower cortisol concentration than
healthy women. Following exercise training program, women with shoulder/neck pain had less
circulating substance P (and possibly glutamate)
and greater circulating concentrations on βE and
cortisol as well as reduced pain intensity and
higher pain pressure thresholds. The researchers
suggested that exercise training could alter pain
intensity and sensitivity as well as peripheral substances related to pain. This study provides more
suggestive effects of opioid-mediated pain modification following exercise training.
In a study conducted on coronary artery
bypass graft surgery patients, transcutaneous
electrical nerve stimulation (TENS) or sham
TENS was applied over the posterior cervical
region (C7-T4) to access the stellate ganglion
region, 5 days after surgery [20]. The treatment
was conducted four times per day for 30 minutes
per session. Patients who had TENS treatment
reported less postoperative pain and had less opiate requirements with higher circulating βE. They
also had greater limb blood flow during a sympathetic stimulation (cold pressor) procedure. Thus,
TENS, which elicits muscle contractions, appears
to increase circulating βE which could lead to
pain reduction.
dvanced Techniques to Investigate
A
β-Endorphin and Pain
Thermal heat pain challenges were employed
before and after running and walking trials to
determine the effects of exercise intensity on pain
[155]. The pattern of pain-related activity in
response to heat/pain treatment using fMRI analysis was compared. The medial and lateral pain
systems and periaqueductal gray (PAG) were key
areas of the descending antinociceptive pathway
that were evaluated. Running reduced affective
A. H. Goldfarb et al.
32
pain ratings whereas walking did not. fMRI
revealed that there was a reduction in pain activation in the PAG with decreases after running but
pain activation was elevated after walking. For
the pregenual anterior cingulate cortex and middle insular cortex there were similar trends of
activation for running vs. walking. Importantly,
the authors concluded that increased circulating
βE levels that were noted with running, but not
walking suggested involvement of the opioidergic system. Another study which utilized fMRI
examined pain modulation in athletes both before
and after running or walking [147]. They examined both PAG and pain ratings and noted
enhanced antinociceptive mechanisms were
attenuated by running (23 km, HR = 148) but not
walking (10 km, HR = 84). Elevated plasma beta-­
endorphins were reported only after running.
These results support previous studies that indicated sufficient exercise intensity and duration
are needed to influence blood beta-endorphin levels. A recent fMRI study reported that resistance
exercise training (twice per week for 15 weeks)
in fibromyalgia patients did not significantly alter
distraction-induced analgesia nor influence brain
activity [115]. This group previously reported the
influence of resistance exercise training in a
larger cohort of subjects [105].
responsible for pain reduction following bouts of
exercise. The most commonly proposed mechanism includes activation of the endogenous opioid system, in particular the release of βE with
the CNS [66] and from muscle contractions during intense exercise stimulating pain receptors in
skeletal muscle which can stimulate the endogenous opioid system [163]. However, previous
research on humans and animals has been unclear
regarding the involvement of the endogenous
opioid system in EIH after opioid antagonist
administration [91]. In animal studies, the opioid
antagonists attenuated the hypoalgesic effect of
exercise whereas human studies have produced
conflicting results [91]. Therefore, further investigation into the role of endorphins in EIH is warranted to address the inconsistent findings in the
literature.
Recent Pain Models
In a recent review, it was determined that
increased pain threshold following exercise was
attributed to release of endogenous opioids [127].
More specifically, EIH was demonstrated in
healthy participants due to activation of μ-opioid
receptors both peripherally and centrally.
However, evidence of EIH in individuals with
chronic pain has been equivocal. Research has
Role of Enkephalins
indicated that exercise of many modalities can
decrease pain symptoms, resulting in improved
It is possible that enkephalin peptides play a role daily function for individuals who suffer from
in altering pain sensation. Exercise- or ischemia-­ chronic pain [17, 30, 51, 58, 113, 116, 147]. In
induced enkephalin release from selected tissues contrast, exercise may not produce pain facilitawas examined in rat, mouse, pig, and human tis- tion in certain chronic pain groups [127]. For
sues [26]. Using real-time PCR, Western blot example, patients with fibromyalgia, whiplash,
analysis, ELISA, and immunofluorescence and chronic fatigue all demonstrate pain sensitivmicroscopy, they reported extensive expression ity following exercise [52, 104, 119, 168, 169].
of preproenkephalin mRNA as well as enkepha- Nijs et al. suggested that these patients had “dyslin precursor protein proenkephalin. Isolated functional endogenous analgesia” in response to
ex vivo tissue that were analyzed revealed that exercise resulting in abnormalities in the central
skeletal muscle, heart muscle, and intestinal tis- pain modulation system, which includes βE
sue released enkephalins. The investigators con- [127]. While this topic has been extensively
cluded that non-neuronal tissues could aid in investigated over the last 20 years, research has
inducing local and systemic enkephalin effects.
mainly focused on the hypoalgesic effects of
From a physiological standpoint, most exercise following a single episode of exercise as
researchers fail to agree on the exact mechanism(s) a result of increases in endogenous opioids [89].
2
Endogenous Opiates and Exercise-Related Hypoalgesia
Current research should focus on the effects of
repeated exercise on chronic pain and attempt to
discover the mechanisms responsible. It has been
hypothesized that regular aerobic exercise leads
to sustained reversal of neuropathic pain by activating endogenous opioid-mediated pain modulatory systems [157]. Following nerve ligation,
rats displayed thermal and mechanical sensitivities that were attenuated within 3 weeks of exercise training [155]. However, hyperalgesia
returned 5 days after cessation of exercise. These
authors provided evidence of βE and met-­
enkephalin involvement and injected naltrexone
into the intracerebroventricular region which
reversed EIH. Recent studies have indicated
increased βE and met-enkephalin in the medulla
and periaqueductal gray area, regions of the brain
that are also involved in the descending pain
pathway.
Conclusion
Exercise of sufficient intensity and duration can
induce transient pain modification, but more
evidence is needed to substantiate the role of
agents that are involved in triggering the mechanisms of action in EIH. βE can bind to various
opioid receptors within the CNS and can modify
pain. However, it is unclear if these actions are
solely dependent to induce the EIH and if these
actions reside exclusively within the CNS or are
also triggered by agents outside the CNS such
as signals arising from exercising muscles to
help alleviate pain. In addition, not all individuals may respond in a similar manner, thus the
proposed mechanisms explaining why EIH may
work in some and not others, needs further
clarification.
Summary
In conclusion, exercise of sufficient intensity and
duration may influence the endogenous opioids,
but what is measured in the circulation does not
necessarily reflect what occurs within the brain.
Numerous factors such as sex, menstrual cycle,
33
diet, plasma volume, carbohydrate level, and
inflammation can influence the endogenous opioids. Furthermore, immune function and neural
control can clearly alter endogenous opioid activity. Finally, a greater understanding of the influence of exercise on the endogenous opioid effects
in the brain needs to be established.
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3
The Effect of Exercise
on the Hypothalamic-PituitaryAdrenal Axis
David H. St-Pierre and Denis Richard
The HPA Axis
Introduction
Over the last decades, important discoveries have
allowed exercise science to bloom as a research
field. Practical applications in kinesiology influence a wide range of populations including individuals with diverse degrees of disabilities to
high-performance athletes. Important advances
include the optimization of training techniques,
biomechanics, motor skills, periodization, and
injury prevention. Sports psychology is another
emerging discipline recognized to have a profound impact on active individuals in terms of
adherence and compliance to a training program
as well as physical improvements and raw performance. As for injury prevention, it is now generally accepted that physical activity must be
performed in an equilibrated way in order to
maximize the desire to pursue while reducing the
risks of nonadherence, of non-compliance, and of
developing psychological disorders. Since its
discovery, the hypothalamic-pituitary-adrenal
D. H. St-Pierre (*)
Department of Exercise Science, Département des
Sciences de l’activité Physique, Université du Québec
à Montréal (UQAM), Montréal, QC, Canada
e-mail: st-pierre.david_h@uqam.ca
D. Richard
Quebec Heart and Lung Institute Research Center,
Laval University Obesity Research Chair, Québec,
QC, Canada
(HPA) axis was shown to play a major role in the
control of anxiogenic and depressive behaviors.
A growing evidence indicate that exercise exerts
acute and chronic effects on the HPA axis.
However, the mechanisms through which it influences the HPA axis, and vice versa, remain to be
clarified. To add to the complexity, a wide range
of HPA axis responses are reported in different
populations. These are generally proposed to
depend on the type of physical activity, the intensity, and the volume at which it is achieved.
Hence, overtraining and the dynamic progression
of performance could also influence the relationship between exercise and the HPA axis. The
present chapter will review the current state of
knowledge to clarify how exercise influences the
HPA axis.
Defining the HPA Axis
The HPA axis consists of three structurally independent components including the hypothalamus, the anterior pituitary, and the adrenal cortex
(see Fig. 3.1). These structures are intimately
interacting through the release of neuroendocrine messengers. In the medial parvocellular
and the magnocellular parts of the paraventricular nucleus of the hypothalamus (PVH),
corticotropin-­releasing factor [CRF, a 41-amino
acid (aa) peptide] and arginine vasopressin (AVP,
expressed in approximately half of the CRF neurons) are synthesized [1]. CRF neurons project
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_3
41
D. H. St-Pierre and D. Richard
42
Exercise
(+)
Ghrelin
PACAP
(-)
Hypothalamus
Stress
Pituitary
(+)
CRF
(+)
BDNF
(+)
AVP
IL-1b, IL-1, IL-6,
and TNF-a
Hypothalamus
(+)
(-)
AVP
CRF
(+)
Portal system
Anterior pituitary
Immune
cells
(+)
Hypothalamic
neurons
Metabolic
effects
Corticotrophic cells
Blood
circulation
(-)
ACTH
Systemic circulation
Endotoxins
(+)
NOS
GABA
serotonin
(+)
Cortex
Medulla
Glucocorticoids
(+)
ACTH
Receptors
(MC2R)
Adrenal gland
Fig. 3.1 The three structurally independent components of the hypothalamic-pituitary-adrenal (HPA) which include
the hypothalamus, the anterior pituitary, and the adrenal cortex
to the exterior layer of the median eminence and
release CRF into the portal circulation until they
subsequently reach corticotroph cells from the
anterior pituitary to stimulate the secretion of
adrenocorticotropic hormone (ACTH). In turn,
ACTH is released and transported via the general circulation to activate the adrenal secretion
of glucocorticoids. Importantly, it is known that
glucocorticoids negatively control pituitary corticotrophs and PVH CRF neurons through direct
or hippocampus-mediated feedback inhibition
mechanisms [2, 3].
In mammals, the CRF system is not limited to
PVH CRF neurons. The system also comprises
two CRF receptor types (CRF-R1 and CRF-R2)
[4], a CRF-binding protein [5] and endogenous
CRF receptor ligands, that include mammalian
peptides CRF [6], urocortin (UCN) [7], UCN II
[8, 9], and UCN III [9, 10]. In the brain, the broad
distribution of CRFergic cells, UCNergic neurons, and CRF receptors is compatible with the
main functions attributed to the CRF system [11].
Central administration of CRF evokes autonomic
responses [2, 3], general arousal [12], as well as
anxiety-like behaviors [3, 13]. Furthermore, central CRF injections also activate the sympathetic
while inhibiting the parasympathetic branches of
the autonomic nervous system by stimulating
cardiorespiratory functions [14] and reducing the
activity of the digestive system [15]. Because of
their selectivity for CRF-R2, UCN II and UCN
III [10] (also referred to stresscopin in humans)
have been described as “stress-coping” peptides
capable of exerting anxiolytic effects [9].
AVP is a 9-amino acid (aa) peptide with a
disulfide bridge that is mainly secreted from the
magnocellular cells of the supraoptic nucleus and
the PVH and transported to the circulation to
3
The Effect of Exercise on the Hypothalamic-Pituitary-Adrenal Axis
exert its effects on kidneys and blood vessels [16,
17]. In addition, AVP’s expression is also reported
in the parvocellular neurons of the bed nucleus of
the stria terminalis, the medial amygdala, the
suprachiasmatic nucleus, and the PVH [18–20].
Three major types of AVP receptors are known:
AVPR1a, AVPR1b, and AVPR2 [21, 22]. The
activation of AVPR1b in the anterior pituitary
stimulates the release of ACTH [23], while
AVPR1a and AVPR2 are mainly expressed in the
kidneys and blood vessels [24].
ACTH is a 39 aa peptide derived from the proteolytic cleavage of the proopiomelanocortin
(POMC) gene [25–27]. The expression of ACTH
is modulated positively by CRF and AVP, naloxone, interleukins (IL) IL-1 and IL-6, as well as
leukemia inhibitory factor (LIF), but negatively
by glucocorticoids [28–32]. However, other factors such as pituitary adenylate cyclase-activating
peptide (PACAP), catecholamines, ghrelin, nitric
oxide synthase (NOS), dihydroxyphenylalanine
(DOPA), serotonin, and γ-aminobutyric acid
(GABA) are also suspected to influence ACTH
secretion through still ill-defined mechanisms
[33–35]. ACTH is released in a pulsatile manner
and has been shown to be regulated through a
calcium-dependent mechanism [36]. It is subsequently transported in the circulation to activate
the melanocortin type 2 receptor (MC2R) from
the adrenal glands [37, 38] and, ultimately, stimulate species-specific glucocorticoid (either cortisol in human, nonhuman primates, pigs, and
dogs or corticosterone in laboratory rodents such
as rats and mice) synthesis and secretion [39]. In
a matter of seconds to minutes, the release of glucocorticoids from adrenal glands will activate
glucocorticoid receptors (GR), stimulate annexin
1 (ANXA1) production, and, consequently, block
CRF-induced ACTH secretion [40, 41]. It is however suggested that the level of complexity of the
direct and indirect mechanisms through which
glucocorticoids exert their repressive effects on
the HPA is much higher than what was anticipated during the 1980s [1].
Other mediators of the HPA axis were identified over the last decades. For instance, the gut
microbiota is now proposed to influence anxiogenic and depressive behaviors via its effects on
43
the HPA axis. Germ-free (absence of gut microbiota) chronically restrained mice display antianxiety behaviors but increased CRF, ACTH,
cortisol, and aldosterone levels in hypothalamic
tissues compared to specific pathogen-free
microbiota mice [42–45]. Although the microbial
mechanisms influencing these effects remain ill-­
defined, it is proposed to regulate glucocorticoid
receptor sensitivity (Fkbp5), steroidogenesis
(MC2R, StaR, Cyp11a1), and catecholamine
synthesis (TH, PNMT) [46]. Hence, colon
expression of 11-β hydroxysteroid dehydrogenase 1 (11HSD-1), CRF, urocortin II and its
receptor, and CRFR2 as well as cytokines TNFα,
INFγ, IL-4, IL-5, IL-6, IL-10, IL-13, and IL-17 is
also reported to be modulated by the microbiota.
As recently evidenced, there is an intimate
link between the regulation of the HPA axis and
inflammatory cytokines [47]. For instance, interleukin 1β (IL-1β) is reported to influence the
release of CRF in the hypothalamus, ACTH in
the pituitary, and glucocorticoids in the adrenal
cortex [48–53]. It was also reviewed that IL-6
and TNF-α promote the activation of the HPA
axis [54]. Some of these effects are mediated
through the activation of cyclooxygenase
enzymes (prostaglandins) as well as by brain
nitric oxide, noradrenaline, and serotonin production [55]. Interestingly, the translocation of
endotoxins (derived from Gram-negative microbial components such as lipopolysaccharides/
LPS and others) was previously shown to activate
the HPA axis through the release of IL-1, IL-6,
and TNF-α [56]. This reinforces the existence of
an intimate relation between the gut (and the
microbiota) and the brain for the regulation of the
HPA axis.
Brain-derived neurotrophic factor (BDNF) is
another factor with an influence on the HPA axis.
For example, a single bout of exercise was shown
to stimulate hippocampal BDNF expression in
mice [57]. In humans, carriers of the Val66Met
BDNF allele (prevalence of up to 50% and 32%
in Asians and Caucasians, respectively [58])
were shown to display increased HPA axis activity through a higher cortisol response to stress
[59, 60]. Expression of BDNF is co-localized
with CRF and AVP in the PVH and the lateral
44
ventricle [61]. Hence, BDNF administrations
increased the expression of CRF while exerting
the opposite effect on AVP in the parvocellular
and magnocellular PVH portions. Hence this
treatment was likely to promote CRF secretion
since its levels were decreased, while those of
AVP were higher in the hypothalamus. This
hypothesis is supported by the fact that the
administration of BDNF also upregulated ACTH
and corticosterone plasma concentrations.
The HPA Axis and Exercise
Endurance Training
The effect of endurance training on the activation
of the HPA axis has been investigated extensively
in animal and human models. In pigs submitted
to a high-fat diet, a 200% increase in free fatty
acid (FFA) levels is related to a 40% decrease in
ACTH concentrations in response to stress [62].
In the same study, pigs submitted to an endurance
training program displayed a 60% increase in
ACTH following a stress challenge; this effect
was associated with a 56% decrease in FFA without other changes in body composition and insulin sensitivity. In another study, rats confined to a
cage that allowed voluntary wheel running, corticosterone responses to various stimulatory challenges of the HPA axis were shown to be
significantly higher than in untrained animals
[63, 64]. Interestingly, this enhanced adrenal sensitivity to ACTH was completely restored to normal following 5–8 weeks of exercise training. In
an ovine model, ACTH levels were found to rise
in response to exercise, even though the animals
had been previously submitted to a CRF infusion
[65]. The latter suggests that ACTH release could
be stimulated by other factor than CRF, and the
authors suggested AVP as a plausible candidate.
Endurance training upregulated mRNA expression of BDNF and its receptor TrkB in the hippocampus, midbrain, and striatum while
increasing BDNF levels in the hippocampus and
striatum in rats [66]. On the other hand, sprint
interval training was more effective to enhance
BDNF brain content than intensive endurance
D. H. St-Pierre and D. Richard
training in rats [67]. These increased BDNF levels in the brain were also shown to be associated
with reduced anxiety- and depression-like behaviors in tested animals.
In human studies, the activation of the HPA
axis in response to physical activity has been
abundantly reported. For instance, individuals
submitted to chronic endurance training displayed higher hair cortisol [68]. In endurance-­
trained men, after a day without physical exercise,
ACTH and cortisol concentrations were similar
to those of untrained controls [69]. For most of
these athletes, dexamethasone (a synthetic agonist of the glucocorticoid receptor) was not found
to influence the activity of the HPA axis; however, in contrast to untrained subjects, a subsequent administration of CRF was shown to
increase cortisol levels. On the other hand, obese
adolescents submitted to a chronic physical activity program displayed a marginal decrease in glucocorticoid sensitivity and increased levels of
glucocorticoid receptor-α (GR-α) expression in
blood mononuclear cells [70]. In young men who
were previously undergoing a strength training
program, cortisol responses were significantly
increased when submitted to higher frequencies
of endurance training [71]. Twenty weeks of
endurance training were also shown to decrease
basal cortisol levels [72]. Hence, the magnitude
of the reduction in cortisol levels was significantly associated with increases in local skeletal
muscle endurance. As observed in animals,
endurance training also significantly upregulated
basal BDNF circulating levels in healthy sedentary or physically active males, and the authors
suggest that this effect could promote brain health
in these populations [73, 74].
The influence of an acute bout of endurance
exercise on HPA axis activity has also been investigated in a multitude of studies. In response to a
walk on a treadmill until exhaustion at 40 °C, circulating levels of cortisol were higher in trained
than in untrained individuals, while those of
ACTH were not different [75]. Interestingly, in
response to the same challenge in trained and
untrained individuals, ACTH, norepinephrine,
and dehydroepiandrosterone-sulfate (DHEA-S)
levels were significantly increased, while those
3
The Effect of Exercise on the Hypothalamic-Pituitary-Adrenal Axis
of growth hormones (GHs), aldosterone and epinephrine, were initially elevated but reached a
maximal value (plateau) at 38.5 °C. In athletes
submitted to a strenuous exercise, CRF and cortisol responses to HPA activation were not blunted
by physiological endogenous hypercortisolism,
and this suggests that pituitary sensitivity is
decreased in response to the feedback inhibition
induced by cortisol [76]. As noted, acute physical
activity has been reported to influence HPA axis
activity; however, the relevance of considering
other physiological conditions should not be
neglected. In fasting subjects submitted to physical exhaustion, ACTH and cortisol levels significantly increased in hypoglycemic conditions, but
this effect was abolished when pretest glycemic
levels were maintained [77]. This also suggests
the relevance of further examining the HPA axis
activation under hypoglycemia.
While the abovementioned information indicates that HPA axis activity is modulated by
chronic and acute training, it is also important to
evaluate the effect of a recuperation phase. In
runners, it has been observed that cortisol and
ACTH levels are significantly lower 2 days following a marathon, while whole body 11β-­HSD-­1
and ghrelin levels are upregulated [78]. Also, the
suppression of cortisol in response to a dexamethasone challenge is strongly increased after
6 weeks of reduced training.
Resistance Training
Although the effect of endurance training on the
activation of the HPA axis is abundantly
described, fewer studies have evaluated the
effect of resistance training. Resistance training
can be defined as any exercise program using
one or multiple training strategies (own body
mass, free weights, or diverse exercising
machines), to enhance health, fitness, and performance [79]. In healthy untrained men submitted to acute resistance training, cortisol
concentrations were not modulated [80].
However, in the same subjects, catecholamines,
lactate, TNF-α, IL-2, and epidermal growth factor (EGF) levels increased, while monocyte che-
45
motactic protein-1 (MCP-1) concentrations
decreased. Furthermore, a positive correlation
was observed between the concentrations of cortisol and TNF-α. Interestingly, the type and the
intensity at which resistance training is performed are suggested to influence the HPA axis.
In competitive athletes performing in muscular
power disciplines (alpine ski, bodybuilding, and
volleyball), an isokinetic exercise induced higher
acute increases in ACTH, cortisol, and lactate
than in endurance athletes (marathon, triathlon,
cross-country skiing, and rowing) [81]. However,
this effect was not observed during the recovery
period. The type of training is reported to influence the activation of the HPA axis; however the
effects of the intensity and volume of resistance
training needed to be clarified. Interestingly, significantly lower cortisol levels were measured
after a single bout of high-­intensity resistance
training (HIT) then after performing a traditional
3-set protocol in male college students [82].
Age, gender, circadian rhythm, and body composition are other factors that are often reported
to influence hormonal secretions (see Copeland,
Chap. 23 in this book). Studies were conducted to
clarify the effects of age, gender, circadian
rhythm, and body composition on the activation
of the HPA axis. Young and middle-aged men
were submitted to an 8-week resistance training
program which was shown to decrease both basal
cortisol and ACTH levels [83]. However, age did
not have a significant influence on the results. In
contrast, 9 weeks of combined endurance and
resistance training was shown to increase cortisol
levels by 23% in young sedentary women, but
this effect was not observed in their male counterparts [84]. This suggested that women undergoing physical training are more sensitive to the
activation of the HPA axis than males. To determine the role of the circadian rhythm on the activation of the HPA axis, trained subjects were
instructed to perform the same resistance training
session at three time periods over different days.
Cortisol levels were higher in the morning but
decreased 3 min and up to 48 h after performing
their bout of exercise [85]. This indicated the
importance of considering the time at which
blood samples are collected before, during, and
46
after undergoing a session of resistance training.
Contrastingly, after submitting untrained young
males to 11 weeks of resistance training, the time
of the day at which exercises were performed did
not influence the levels of hormones of the HPA
axis [86]. However, the same authors reported
that postexercise cortisol levels were lower than
basal concentrations. To determine the effects of
body composition on the activation of the HPA
axis, normal weight and obese individuals were
submitted to resistance training. Cortisol levels
were significantly different between normal
weight and obese individuals [87]. This suggested that body composition may also modulate
the HPA axis.
Different types of resistance training promote
skeletal muscle hypertrophy or strength.
Untrained young male and female adults were
recruited to clarify the different effects of the two
types of resistance training on the HPA axis.
While performing the experimental protocol, significantly higher BDNF levels were measured
during the exercise designed to promote hypertrophy than the one intended to increase strength
[88]. In trained men, BDNF levels increased similarly in response to the different intensity and
volume levels of resistance training [89]. In older
adults submitted to various loads of resistance
training, BDNF levels increased in male participants, while no effects could be detected in
female individuals [90]. These data support the
hypothesis that the HPA axis activation might be
influenced by the type of training, the intensity,
the post-training period, and body mass but not
by age or the time of the day at which it is performed. These latter issues are in need of further
investigations to clarify aspects of the contradictory results.
I ntensity of Physical Activity and HPA
Axis Activation
It is profusely reported that the HPA axis is activated in response to physical activity, and different levels of exercise intensity were also shown to
have an important impact. In mice submitted to
acute psychological stress, high-intensity physi-
D. H. St-Pierre and D. Richard
cal activity increased cortisol, IL-1β, IL-2, and
IL-6 while decreasing ACTH-positive cells in the
pituitary [91]. Although collected in animals,
these results indicated the relevance of considering the intensity of physical activity, and this was
also investigated in human models. For instance,
it was initially proposed that cortisol levels are
increased by 60 min of running on a treadmill at
a threshold intensity of 60% of the VO2max [92].
Moderately trained men also displayed a significant increase in cortisol after performing 30 min
of exercise at 60% and 80% of their VO2max, while
ACTH levels were only elevated at the highest
intensity [93]. In endurance-trained males,
30 min of exercise on a cycle ergometer, significant increases in cortisol were only observed at
80% of the VO2max both in saliva serum [94].
Interestingly, the same authors observed that
peak cortisol levels were only monitored 30 min
after the cessation of the physical activity. When
compared to low-intensity, high-intensity cycling
caused similar increases in BDNF and cortisol
levels in both participants with or without depression [95]. In trained athletes submitted to a prolonged high-intensity exercise, increased plasma
concentrations of cortisol, ACTH, CRF, and AVP
were observed [96]. It was also reported that the
rise in osmolality observed during exercise correlates with increases in plasma AVP. Furthermore,
for a given type of physical activity, high-­intensity
and prolonged duration respectively increased
AVP and CRF levels. In healthy participants
administered with dexamethasone (4 mg), performing physical activity at the highest intensity
(90% vs. 100% maximal aerobic capacity) caused
a significant raise in ACTH, cortisol, and AVP
circulating levels [97]. Interestingly, this response
was shown to be amplified in women with regard
to the one observed in men. Interestingly, high-­
intensity interval training was shown to increase
BDNF levels to a higher magnitude than continuous moderate-intensity exercises in obese individuals [98]. This suggests that short and intense
bouts of exercise could exert beneficial effects to
individuals intending to design and/or perform
physical activity programs.
While the effect of exercise intensity was evaluated in response to distinct physical activities,
3
The Effect of Exercise on the Hypothalamic-Pituitary-Adrenal Axis
another group compared occupational differences between workers performing high-­intensity
duties (slaughterhouse workers) and others
achieving low-intensity tasks (office workers)
[99]. Slaughterhouse workers displayed higher
levels of ACTH, total peroxides, antioxidant
capacity, oxidative stress index, and c-reactive
protein (CRP), while their levels of endogenous
peroxidase activity, polyphenols, and BDNF
were reduced. These results were even affected
by the duration of the work shifts in slaughterhouse workers since higher CRP and lower
BDNF levels were measured after completing
12 h vs. 8 h shifts.
Results presented in this section clearly indicate that the intensity and the volume of a physical activity, the fitness level, and the type of
exercise performed by an individual have a direct
impact on the activation of the HPA axis. In turn,
this should be taken into consideration when
elaborating training programs.
Highly Trained and Elite Athletes
Overall, the increased activity of the HPA axis in
highly trained athletes could have important
implications on their somatic and mental health.
During a progressive stress test until exhaustion
on a treadmill, cortisol levels were higher from
baseline to the initiation of recuperation in professional athletes than in controls [100].
Interestingly, hormonal levels were regularized
over the recuperation period. In ultramarathon
runners, cortisol levels were at their highest at the
completion of a 622 km race, and levels were
only normalized after 6 days of recovery [101].
In highly trained athletes, the morning surge in
ACTH and cortisol was observed earlier, and
ACTH levels were significantly higher than in
normal individuals [102]. In addition, the stimulation of CRF and ACTH release was more pronounced in highly trained athletes than in
untrained individuals following the administration of the nonselective opioid receptor antagonist naloxone [32]. Altered HPA axis functions
were also observed in elite athletes. For instance,
artistic gymnasts competing at the European
47
Championships displayed higher salivary cortisol
concentrations and more important levels of psychological stress than controls [103]. In addition,
higher psychological stress and saliva cortisol
levels were also observed in female vs. male athletes. In elite junior soccer players, nonfunctional
overreaching performances were associated with
higher scores of depression and angriness,
whereas resting GH and ACTH concentrations
after maximal effort were diminished [104].
These observations could be associated with the
decreased expression of GR-α mRNA in highly
trained individuals and with lower increases in
atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) levels in response to exercise [105–110]. These elements suggest the
influence of the HPA axis on stress and emotional
status. Ultimately these factors could also have a
major incidence on sportive performances in elite
athletes.
Overtraining
The available information regarding altered HPA
axis functions in athletes suggests the relevance
of considering potentially for pathological conditions such as overtraining. In rats submitted to
daily swimming bouts of 45 min 5 days per week
for 2, 4, or 6 weeks, corticosterone gradually
increased. In parallel both basal ACTH and corticosterone plasma levels increased until they
reached a plateau after 6 weeks of swimming
[111]. Hence, in the PVN and the pituitary of the
same animals, mRNA expression of the glucocorticoid receptor decreased, while the one of
CRF transiently increased. While these results
are interesting, it is difficult to determine whether
the important volume of exercise to which rats
were submitted can be considered as overtraining. These results raise important questions since
cortisol levels were significantly below normal
in overtrained Standardbred racehorses [112,
113]. Interestingly, these discrepancies may be
species-­
specific or be related to the duration
overtraining in the animals. In other words, rats
submitted to swimming may still have the capacity to produce corticosterone, while Standardbred
D. H. St-Pierre and D. Richard
48
racehorses may have been submitted to a chronic
overactivation of the HPA axis which led to
impairments in their capacities to secrete cortisol
before being diagnosed. In different populations
of human athletes, several alternative methods
such as a CRF stimulation test (evaluation of
basal ACTH concentrations and GH pulsatility),
free testosterone over cortisol concentrations,
low basal cortisol levels, as well as HPA
responses to two standardized exercise tests
were proposed for the diagnostic of overtraining
[114–116]. For instance, in response to two
acute bouts of exercise, increased prolactin
(PRL) levels and decreased ACTH concentrations are reported in overtrained athletes [117–
119]. These effects could be mediated by the
repetitive occurrence of muscle and skeletal
trauma resulting in local inflammation and, consequently, in a systemic inflammatory responses
which, in turn, could yield to impairments of
athletic performances [115].
Postexercise Recuperation
Depending on the type of physical activity and its
intensity and volume, it is critical to allow the
body to recuperate, replenish its energy reserves,
and resynthesize injured tissues in order to
improve athletic performance. Recuperation is
well-characterized in nutrition and physiology;
however, it is another factor to take into consideration when considering the effects of exercise on
the HPA axis. For instance, it was shown that the
carbohydrate/electrolyte consumption right after
performing a bout of high-intensity physical
activity significantly reduced blood cortisol levels in male athletes [120]. However, the hydration status, per se, was not associated with an
alteration of circulating cortisol concentrations
[121]. In rugby players submitted to a magnesium supplementation, significantly higher
ACTH but decreased cortisol levels were
observed compared to the same type of participants given a placebo [122]. In addition, magnesium supplementation abolished the post-game
increase in IL-6 while reducing the increase in
neutrophil/lymphocyte ratio.
emory, Defeat, Fear, and Cognitive
M
Functions
During a physical activity, the capacity to remember how to optimally perform an exercise as well
as the bad feelings and the fear of defeat or mishaps occurring during the event may have profound effects on an individual’s performance.
Because of obvious ethical reasons, this is difficult to investigate in humans. However, rodent
models were used to investigate the effect of the
HPA axis on memory, defeat, and fear. In rats
administered with metyrapone (a corticosterone
synthesis disruptor), impaired traces of fear conditioning have been observed [123]. A number of
studies also evaluated the effects of CRF on
defeat conditioning as well as on memory. The
central administration of anti-sauvagine-30 (a
CRF-R2 receptor antagonist) reduced submissive
and defensive behaviors induced by territorial
aggression conditioning in Syrian hamsters
[124]. However this effect was not observed in
response to neither metyrapone nor CP-154,526
(a CRF-R1 antagonist) administrations in the lateral ventricle of rats increased spatial memory
through a β-adrenergic-dependent mechanism
[125]. Also, central administrations of NBI30775
(CRF-R1 antagonist) prevented stress-induced
hippocampal dendritic spine loss while restoring
stress-impaired cognitive functions [126]. This
suggests that stress-induced central effects are
mediated through the activation of CRF-R1.
These discoveries are important since they could
allow the implementation of targeted interventions or pharmacological treatments to reduce the
fear of defeat or the occurring of an injury in individuals or athletes who previously encountered
such negative experiences. In turn, this would
allow preventing the adverse outcomes on their
athletic performances.
Conclusion
The last paragraphs have underlined the importance of the HPA axis on the regulation of moods
and behaviors in animals and humans undergoing
physical activity. Depending on the population of
3
The Effect of Exercise on the Hypothalamic-Pituitary-Adrenal Axis
interest and the objectives to be reached, it is
critical to adapt training programs to maximize
their benefits while minimizing the risk of developing anxiety and depression. This has to be
applied to athletes as well as other populations
with different levels of fitness and/or degrees of
disabilities. For instance, professional or Olympic
athletes are particularly at risk of overtraining,
and their moods, cognitive functions, and confidence levels have an important impact on their
performances. Physical activity is also an important element of a healthy lifestyle to prevent and/
or counteract the dreadful effects of obesity and
ensuing metabolic dysfunctions that have reached
epidemic levels in North American populations.
In obese individuals, adherence and compliance
to training programs remain major obstacles. For
athletes or obese individuals, a better understanding on how exercise modulates the HPA axis will
provide essential tools to develop novel training
approaches. As one consequence of this, it will be
essential to exhaustively characterize individuals
undergoing an exercise program in order to determine their levels of fitness; the type, intensity,
and volume of physical activity required; as well
as the window of time over which objectives need
to be achieved. It is also important to constantly
monitor exercising individuals since adaptation
to the training planification will be required as
soon as anxiogenic or depressive behaviors will
be present. Hence, distinct factors of the HPA
axis may be used as sensitive biomarkers to
detect disorders before clinical symptoms can be
detected. Globally, this indicates the relevance of
including parameters of the HPA axis as modulators of anxiety and depressive behaviors in exercising individuals. In sum, while it remains a
precarious equilibrium, it suggests that elements
of the HPA axis must be taken into consideration
along with the assessment of an individual’s
physical capacities when designing a training
program. Consequently, while the planification
and periodization must be optimized, it is important to adapt the program accordingly in function
of early signs of anxiogenic or depressive behaviors. Ultimately, this will be more effective at
yielding improvements in athletic performance
and health benefits than the simple addition of
49
strenuous exercises that could provoke the premature interruption or to slow down physical
training program for various clinical reasons.
Our current knowledge of the relationship
between the HPA axis and physical exercise
reviewed in the above paragraphs clearly highlights the importance of adequate preparation for
exercise. Also, a number of data indicate that
complex molecular and cellular mechanisms
intervene in highly trained athletes that do not
occur in normal individuals. As a whole, the
above information suggests that the HPA axis
importantly influences stress-induced functions
and that the intensity of HPA axis activation is
intimately related to the type of training, the
intensity, and the volume at which it is performed. This strongly suggests the relevance of
considering the impact of the HPA axis when
elaborating training programs in different types
of individuals.
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4
Impact of Chronic Training
on Pituitary Hormone Secretion
in Humans
Johannes D. Veldhuis and Kohji Yoshida
Introduction
The impact of chronic training on pituitary function is best understood by a basic appraisal of the
neuroendocrine physiology of any given individual axis and the more complex interactive pathophysiology among axes [1–12]. Interaxes
interactions have received relatively little attention. Even evaluating a single neuroendocrine
axis in its dynamic state is a complicated challenge, given combined feedforward and feedback
activities among the key control loci within any
given axis [13, 14]. For example, in the case of
the growth hormone (GH) and insulin-like growth
factor 1 (IGF-1) axis, hypothalamic GH-releasing
hormone (GHRH) secreted by arcuate nuclei
stimulates pituitary GH secretion acutely,
whereas the somatostatinergic system originating
in the paraventricular nuclei opposes GHRH
action [15]. These two neuronal inputs are reciprocally interconnected by intrahypothalamic synapses and common impinging neuromodulator
pathways [14]. In addition, secreted GH feeds
back on brain GH receptors, stimulating soma-
J. D. Veldhuis (*)
Endocrine Research Unit, Mayo Clinic,
Rochester, MN, USA
e-mail: veldhuis.johannes@mayo.edu
K. Yoshida
Department of Obstetrics and Gynecology, University
of Occupational and Environmental Health,
Kitakyushu, Japan
tostatin secretion and possibly inhibiting GHRH
release. Available GH secreted into the bloodstream triggers IGF-1 production in various target tissues, and circulating IGF-1 is capable of
inhibiting pituitary GH secretion indirectly and
directly (see Fig. 4.1). Such feedforward (GHRHs
driving GH secretion) and feedback (GHs inhibiting its own secretion, IGF-1 s inhibiting GH
secretion, and so forth) dynamic control mechanisms in principle can be modified by the effects
of exercise at one or more levels within the axis.
Moreover, multiple determinants modulate neuroendocrine responses to training, such as the
body composition of the individual, concurrent
stress and/or weight loss, gender, diet and energy
balance, concomitant drug or hormone use, age,
puberty, pregnancy, and/or lactational status
[16–18].
Here, we will examine the neuroendocrine
determinants of pituitary responses to exercise
training, explore some of the confounding issues
(e.g., species differences, varying modes of neurohormone secretion, within- and between-axis
regulation, and so on), and explore the overall
notion of neuroendocrine axes as feedback and
feedforward control systems capable of within-­
axis as well as between-axes interactions. Finally,
metabolic mechanisms, although likely multifactorial, will be examined briefly, and their clinical
implications underscored.
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_4
55
J. D. Veldhuis and K. Yoshida
56
GHRHp
SRIHp
FSRIH
FGHRH
Hypothalamus
GHRHs
SRIHs
Elim
GHp
Elim
Pituitary
FGH
GHs
Elim
IGF-Ip
FIGF-I
Systemic
Circulation
IGF-Is
Elim
Fig. 4.1 EU eumenorrheic athletes; AM amenorrheic
athletes; ANX anorexics. Amenorrheic athletes have
endocrine profiles (i.e., decreased thyroid hormones) similar to anorexics with chronic energy deficiency. (Data
taken from Refs. [43, 47]). ∗Eumenorrheic means are significantly different from amenorrheic and anorexic means
(p < 0.05). Panel A = total T3 (triiodothyronine) and panel
B = total T4 (thyroxine)
ultiple Determinants of Pituitary
M
Responses to Exercise Training
training are not necessarily identical [20, 21,
23–30]. Moreover, stress or acute exercise
imposed in an untrained individual will elicit
endocrine responses potentially distinct from
those observed in a highly physically trained
subject [3, 8, 9, 11, 31–40]. Thus, many studies
are confounded in part by the nature of the prior
or concomitant training regimen, its duration,
and its intensity. Finally, extreme physical exertion, “overreaching,” often evokes neuroendocrine disturbances that are not typical of either
short-term submaximal exertion or chronic
training [5, 9, 41–43].
Among other determinants of neuroendocrine
responses to exercise training is the acuteness
vs. chronicity of the training or exercise stimulus [2, 5, 11, 12, 19–22]. In particular, numerous
studies demonstrate that acute exercise induces
a variety of short-term changes in multiple
hypothalamo–pituitary axes, including the
nearly immediate secretion of GH and adrenocorticotrophic hormone (ACTH), β-endorphin,
and cortisol, whereas the results of chronic
4
Impact of Chronic Training on Pituitary Hormone Secretion in Humans
Neuroendocrine axes are exquisitely sensitive to
nutrient intake, body composition, and total (and
percentage) body fat [44–51]. Recent s­ tudies of the
GH axis document unequivocally that percentage
body fat, and in particular visceral (intra-abdominal)
fat accumulation [52], negatively influences pulsatile GH secretion by suppressing the mass of GH
secreted per burst and shortening the half-life of GH
in the circulation [44, 45, 53–56]. The reciprocal
relationship between visceral fat mass and GH
secretion is illustrated in Fig. 4.2. Impaired GH
secretion and more rapid GH removal jointly serve
to reduce 24-h pulsatile serum GH concentrations in
otherwise healthy but relatively more (viscerally)
obese individuals. In contrast, acute weight loss or
nutrient deprivation potently stimulates GH secretion in the human (while suppressing it in the rat) by
3–10-fold, with augmentation in both men and
women of GH secretory pulse amplitude and mass
and, to a lesser degree, burst frequency [47, 57, 58].
Consequently, nutrition, body weight, and body
composition are prime determinants of pituitary
MEAN 24-Hr
Serum GH Concentration (µg/L)
2
57
(GH) secretory activity, which likely condition
responses to exercise [59]. In addition, in men, as
well as more recently recognized in women, body
mass index (relative obesity) is a negative correlate
of LH pulse amplitude [49, 60] and of the serum
testosterone concentration in middle-aged men [49].
Gender distinctions also strongly influence the
secretory output of several neuroendocrine axes.
Foremost, the gonadotropin-releasing hormone–
luteinizing hormone (GnRH–LH) follicle-­
stimulating hormone (FSH)–sex steroid axes in
men and women exhibit clarion differences, particularly at the level of the so-called positive
feedback, which is mechanistically required to
achieve a preovulatory LH surge in women [61].
The GH–IGF-1 axis is also strongly sexually
dimorphic in the human (as well as in the rat, as
reviewed earlier [15]). For example, in healthy
premenopausal men and women, GH secretion
differs quantitatively by way of a nearly twofold
greater mean (24-h) serum GH concentration,
higher plasma IGF-1 level, greater mass of GH
r = -0.68
p < 0.001
female
male
1
0
3
5
4
6
Ln (Intraabdominal Fat) (cm2)
Fig. 4.2 Negative relationship between 24-h mean serum
GH concentration and intra-abdominal (visceral) fat mass,
as determined by computerized axial tomographic scanning of the abdomen, in a cohort of healthy middle-aged
men and women. GH concentrations were determined by
20-min blood sampling for 24 h and subsequent assay by
immunofluorometry. The solid circles denote male subjects, and the open circles females. The regression line
shows a strongly negative relationship between the natural
logarithm of intra-abdominal adiposity and daily GH
secretory activity in both men and women. In multiple linear regression analyses, intra-abdominal fat mass
accounted for the majority of the variability in integrated
serum GH concentrations, exceeding that owing to age
and gender in this population. (Redrawn with permission
from Vahl et al. [56])
J. D. Veldhuis and K. Yoshida
58
secreted per burst, and a more disorderly pattern
of GH release in women compared to men [62].
In addition, the individual negative impact of age,
body mass index, or percentage body fat on GH
secretion is 1.5–2-fold more evident in men than
women [48]; the positive effect of physical conditioning (increased VO2max) on GH release is
also more prominent in the male [48] (Fig. 4.3).
Integrated Serum GH Concentration
(ug/L x min)
Integrated Serum GH Concentration
(ug/L x min)
a
8000
6000
4000
2000
0
15
20
30
25
35
40
Integrated Serum GH Concentration
(ug/L x min)
Integrated Serum GH Concentration
(ug/L x min)
Age (yrs)
8000
6000
4000
2000
0
0
10
30
20
40
50
8000
6000
4000
2000
0
15
20
6000
4000
2000
0
20
30
40
50
60
70
Men
V o 2 Max
Women
40
% Change Per SD
35
VO2 Peak
(ml/kg/min)
60
+33
+17
20
0
30
8000
Percent Body Fat
b
25
BMI
Age
BMI
% Fat
–10
–20
–19
–16
–23
–40
–42
–45
–60
Fig. 4.3 (a) Impact of gender on the effects of age, adiposity as measured by body mass index (BMI) or percentage body fat, and physical fitness as quantitated by
maximal oxygen consumption (VO2max peak or max) on
integrated (24-h) serum GH concentrations in normal men
(filled circles, N = 12) and women (open circles, N = 32).
Linear regression plots are given for each sex. The solid
lines denote regression in men, and the interrupted lines
depict women’s data. (b) Approximately twofold greater
impact of age, BMI, percentage body fat, and VO2max on
240-h mean serum GH concentrations in men than
women. Data are means ± SEM expressed as standardized
regression coefficients for the regression lines in (a). The
gender-specific standardized regression coefficient is the
slope of the linear relationship (given as a percentage)
adjusted per unit standard deviation (SD) of the male or
female group as pertinent. (Redrawn with permission
from Weltman et al. [48])
4
Impact of Chronic Training on Pituitary Hormone Secretion in Humans
The tissue responses to GH also may be sex-­
specific in part, since estrogen can antagonize
GH-driven IGF-1 production by the liver [15].
Consequently, gender must be identified as a
major determinant of neuroendocrine responses
in the GH–IGF-1 axis. Exercise-stimulated GH
secretion may be less gender-dependent [63].
A lesser gender difference is observed for the
corticotropin-releasing hormone (CRH)–arginine
vasopressin (AVP)/ACTH–cortisol axis, where in
the female, relatively increased expression of the
CRH gene and increased adrenal responsiveness
to ACTH are proposed [64]. However, the orderliness of individual 24-h ACTH and cortisol
release (approximate entropy) or their relative
synchrony (crossentropy) in men and women is
similar [65].
Another significant confounding influence on
neuroendocrine axes is age. For example, in the
case of the LH–testosterone axis in men, there is
progressive deterioration of LH or testosterone’s
individual orderliness of release over 24 h and of
LH–testosterone coupling or synchrony, when
assessed by either cross-correlation analysis
(indicating diminished feedforward control) [66]
or cross-approximate entropy (indicating
decreased pattern synchrony within the reproductive axis’ feedback system) [67]. The regularity
of GH or ACTH/cortisol release also deteriorates
with age in men and women [65, 68]. In addition,
in both men and women, there are marked quantitative decreases in overall GH axis secretory
activity, with a progressive fall in plasma IGF-1
and daily GH secretion rates with aging, especially in men compared to women of premenopausal age [44, 45, 48, 54].
Concurrent drug and/or hormone use can also
markedly modify several pituitary-target tissue
axes. For example, prescribed or self-use of anabolic steroids will profoundly suppress LH and
FSH release and reduce levels of endogenous
sex steroids while potentially stimulating the
GH–IGF-1 axis (if aromatizable androgens are
employed) [13, 63, 69–71]. Likewise, the use of
birth control pills in young women stimulates GH
secretion significantly and may produce some
alterations in body composition [72]. At puberty,
when sex steroid hormone secretion changes
59
more dramatically [73, 74], the individual’s GH–
IGF-1 and/or GnRH–LH axis may be uniquely
susceptible to the impact of exercise training (at
least prior to pubertal onset), resulting in a significant delay in sexual maturation and adolescence and possibly reduced predicted adult height
[75] (see Chap. 17; First edition).
We infer that an array of important factors,
such as exercise intensity and duration, its acuteness vs. chronicity, associated weight loss and/or
stress (discussed further below), diet and energy
balance, body composition, gender, age, and maturational status (e.g., prepubertal vs. pubertal),
may all codetermine the neuroendocrine and
pituitary responses to a stress perturbation, such
as exercise.
Other Confounding Issues
One confounding issue experimentally in evaluating the impact of acute or chronic physical
training on pituitary function is species differences. For example, in the rat, physical exertion
reduces GH secretion [15], whereas in the human
acute and chronic exercise, both increase GH
secretion significantly, the former within
15–30 min and the latter following sustained
exercise at an intensity above the individual lactate threshold [15, 20, 21, 24, 76, 77]. Indeed,
chronic physical training in women results in a
doubling of the 24-h mean serum GH level even
on days when exercise is not undertaken [21] (see
Fig. 4.4 [20]). Consequently, many experiments
carried out in the rodent do not find applicability,
especially for the GH–IGF-1 axis, to human studies. Moreover, the gender differences in the GH
axis in the rat and human are readily distinguishable mechanistically in the two species, with a
greater mean amplitude (and mass) of GH
­secretory bursts in women than men (but the converse occurs in the rat) [62]. A similarity in the
two species is a more disorderly pattern of GH
release in the female [78].
Further complicating interpretation and analysis of pituitary secretion are the multifold temporal modes of physiological pituitary hormone
release:
J. D. Veldhuis and K. Yoshida
60
SERUM GROWTH HORMONE CONCENTRATION
(ug/L)
a
BASELINE
30
Control
30
30
• LT
15
15
15
0
0
0
30
30
> LT
1 YEAR
> LT
• LT
15
15
15
0
08:00
30
Control
10:00
0
08:00 08:00
10:00
08:00
0
08:00
10:00
08:00
10:00
08:00
TIME (CLOCKTIME)
b
BASELINE
GROWTH HORMONE SECRETORY RATE
(ug/L/min)
2
Control
2
2
• LT
1
1
1
0
0
0
2
2
> LT
1 YEAR
> LT
• LT
1
1
0
08:00
2
Control
10:00
1
0
08:00 08:00
10:00
08:00
0
08:00
TIME (CLOCKTIME)
Fig. 4.4 The 24-hour serum GH concentration (a) or
secretion rate (b) profiles in three different premenopausal
women each studied twice: control (left; no exercise training, sedentary volunteer); before (baseline) and after
1 year of exercise training below or at the individually
determined lactate threshold (LT) (middle panel; exercise
volunteer #1), and exercise training above the LT (right
panel; exercise volunteer #2). (Adapted with permission
from Ref. [20])
4
Impact of Chronic Training on Pituitary Hormone Secretion in Humans
1. Pulsatile.
2. Nyctohemeral or circadian.
3. Entropic, or moment-to-moment variations in
the orderliness of secretion [67, 79–81].
Cell
In contrast to the foregoing episodic (pulsatile) secretory mode are less rapid, 24-h variations in serum hormone concentrations, which
are well established for ACTH, LH, GH, thyroid-­
stimulating hormone (TSH), prolactin, cortisol,
and so forth [82]. These nyctohemeral (night–
day) variations constitute only a small part of the
total variation in daily neurohormone release.
True circadian rhythms are so-called free-­running
with a periodicity of 24 h, temperature-­
compensated, and susceptible to zeitgebers or
specific phase-entraining cues [83]. Not all
human 24-h neuroendocrine rhythms conform
to this definition, which would denote true
Secretory Velocity
Pulsatile hormone secretion typically mirrors
episodic neural input that acts via intermittent
secretagog delivery to a responsive pituitary cell
population in the absence of significant inhibitory input concurrently. Indeed, a pulse of pituitary hormone secretion can be viewed as a
collection of secretory rates, centered about some
moment in time. This concept is illustrated in
Fig. 4.5.
V1
V2
V3
Vi
Vmax (Amplitude)
Half-duration
Burst Position
Capillary
Time
II
Concentration
*
Time
Concentration
Secretion
61
Time
Time
t
S(z)
Secretion
Function
*
*
E(t-z)
=
S(z)E(t-z)dz
0
Clearance
Function
Fig. 4.5 Schematized illustration of a model-specific
deconvolution concept implemented to quantitate (GH)
secretion. The upper landscape depicts an intuitive formulation of a hormone secretory burst, as arising from
(multi-)cellular discharge of individual hormone molecules more or less in concert temporally, each at its own
particular secretory rate (velocity). A secretory burst (or
pulse) is visualized as an array of such molecular secretory velocities centered about some moment in time and
dispersed around this center with a finite standard duration (SD) or half-width. The burst event may or may not
be symmetric over time. The lower landscape with the
algebraic subheads shows the mathematical notion,
whereby a plasma hormone concentration peak (far right)
=
Convolution
Integral
is viewed as developing from a burst-like secretory process (far left) and a finite hormone-specific removal rate
(half-life of elimination). The so-called convolution
(intertwining or interaction) of the simultaneous secretory
and elimination functions creates a resultant (skewed)
plasma concentration pulse. Deconvolution analysis consists of mathematically estimating the constituent underlying secretory features (and/or associated half-life),
given (a series of) blood hormone concentration peaks as
the starting point. A variety of model-independent
(waveform-­invariant) deconvolution strategies can also be
applied, if a priori knowledge of the pertinent (biexponential) hormone elimination rate process is available.
(Adapted with permission from Ref. [125])
62
(suprachiasmatic nucleus-driven) circadian activity. Based on sleep-reversal studies, and so forth,
circadian rhythmicity clearly does exist for
ACTH/cortisol release in the human and GH
secretion (approx 50% of the 24-h GH rhythm is
sleep- and activity-entrained, and 50% is circadian) [15, 84].
Neurohormone release also exhibits features
of minute-to-minute patterning, serial orderliness, or relative regularity, which can be quantified by an approximate entropy statistic [67, 78].
Higher values of approximate entropy denote
greater disorderliness of hormone release and are
a feature of female GH secretory patterns (compared to male), healthy aging of the human insulin, GH, LH, and ACTH/cortisol axes [54, 65, 67,
78, 85, 86], as well as aldosteronomas [87],
tumoral pituitary hormone secretion (acromegaly, Cushing’s disease, and prolactinomas [65,
88]), and insulin release in type II diabetes mellitus [89, 90]. Thus, entropy measures can identify secretory disturbances complementary to
pulsatile or circadian variations.
The complex mode of pituitary hormone
secretion imposes the need for appropriately rigorous sampling intensity and duration to capture
the pulsatile, circadian, and entropic features, followed by application of relevant analytical tools
appropriately validated under those conditions of
study. Such technical issues have been reviewed
recently [80, 91–93].
Further confounding in the literature arises
because biochemically measurable endocrine
changes do not always imply definite biological
or clinical sequelae. For example, studies of the
thyrotropin-releasing factor (TRH)–TSH–thyroidal
axis have revealed numerous biochemically measurable changes during acute or chronic exercise,
but their clinical sequelae are not known [94].
Similarly, in relation to the male reproductive
axis, a variety of pituitary–gonadal changes are
well established in response to chronic exercise,
such as diminished LH pulse frequency at least in
a subset of men, and relatively decreased spermatogenesis (e.g., a 30–50% decline in sperm
number). However, clinical signs and symptoms
of androgen deficiency rarely, if ever, occur, and
male infertility is not known to be associated with
J. D. Veldhuis and K. Yoshida
chronic physical training [5, 32–35, 43, 95–100].
Finally, multiple hormones are produced by the
anterior pituitary gland, and, as discussed further
below, the corresponding individual axes may
evince significant interactions.
euroendocrine Axes as Feedback
N
and Feedforward Control Systems
As intimated in the Introduction, neuroendocrine
axes should be viewed as dynamic feedforward
and feedback control systems. The term feedforward defines the ability of a secreted agonist to
act on a remote or proximal tissue and evoke a
typically sigmoidal (e.g., log-logistic) dose–
response curve, e.g., as anticipated for GHRHs
acting on somatotrope cells in the anterior pituitary gland, GnRHs acting on gonadotrope cells,
and so forth [15, 101]. Conversely, feedback
denotes the ability of a secreted product from a
target tissue to inhibit the production of the agonistic signal, e.g., testosterone feeds back on
hypothalamic GnRH secretion in the male, IGF-1
feeds back on pituitary somatotrope secretion of
GH, l-thyroxine feeds back on TSH secretion at
the pituitary and hypothalamic levels, and so
forth. As highlighted in Figs. 4.1 and 4.6, both
the GHRH–somatostatin/GH–IGF-1 axis [14]
and the GnRH–LH/FSH/sex steroid [101] axes
should be viewed as complex feedback and feedforward control systems [13, 14, 79, 101–103].
This concept is physiologically critical, since
most pathophysiological stimuli impinge on several points within the feedback control system,
thus impacting on the overall dynamics. Such
system-level responses cannot be observed readily when separated components are studied individually. Similarly, the stress-responsive
ACTH–adrenal axis comprises CRH–AVP/
ACTH–cortisol, with corresponding feedforward
and interactive feedback mechanisms inherent [3,
40, 104].
An important notion in future studies of
chronic exercise effects on the pituitary will be
to limit isolation of individual components of
the axis and rather study the overall axis dynamics. Technology, such as approximate entropy
4
Impact of Chronic Training on Pituitary Hormone Secretion in Humans
(-)
63
Hypothalamus
(-)
H6
(-)
H4 and H5
GnRH
neurons
GnRH
Te
Testis:
Laydig Cell
Time
(+)
Te
H1
(basal Te)
Pituitary
Gland
(-)
H3
LH
Time
(+)
H2
Time
Fig. 4.6 Schematic illustration of the time-delayed negative feedback (−) and positive feedforward (+) within the
human male GnRH–LH–testosterone (Te) axis. The broad
arrows indicate feedforward (+) stimulus-secretion linkages, and the narrow arrows denote feedback (−) inhibi-
tion. The “H” functions are developed further in Ref.
[101] and serve to define the dose–response relationships
at each feedback interface within the axis. (Adapted with
permission from Ref. [101])
[67, 105] and network analysis [14, 101], for
accomplishing the latter is just beginning to
emerge. To date, the vast majority of published
literature (as discussed throughout this volume)
has enunciated changes at individual control
points, which unfortunately subdivides the feedback system artificially and limits insights into
its interactive properties, which function from
minute to minute and day to day.
experimental animals, alterations occur not only
in hypothalamic GHRH and somatostatin gene
expression but also in the GnRH neuronal
ensemble and neuropeptide Y (NPY)- and CRH-­
secreting neurons [104, 106]. In conjunction
with concurrent changes in dietary intake, activity of TRH neurons in the hypothalamus may
also be suppressed (reviewed in Ref. [107]).
Relevantly, these multiple neuronal pathways
are directed by corresponding families of neurotransmitters (e.g., norepinephrine, serotonin,
acetylcholine, and so forth), as well as various
potent neuromodulators (e.g., NPY, galanin, and
so on). Thus, a major focus in understanding the
whole-body neuroendocrine responses of an
intact organism to chronic exercise training
must eventually include the articulation of not
only individual neuronal pathway changes but
also their collective and interconnected alterations owing to common neuromodulatory
Introductions Among
Neuroendocrine Axes
Foremost among the challenges to be addressed
in investigative and clinical neuroendocrine
pathophysiology are the nature and mechanisms
of interaction between two, or among three or
more, neuroendocrine axes. For example, in
relation to chronic exercise or other stressors in
J. D. Veldhuis and K. Yoshida
64
Metabolic Mechanisms
inputs. For example, infusion of leptin, the
product of the ob gene in adipocytes, is capable
of rescuing suppressed hypothalamic TRH
secretion in fasting; relieving inhibited GnRH
gene expression in certain stress models; and
stimulating GH secretion in the fasted male rat
(presumptively by reducing hypothalamic
somatostatin gene expression). Thereby, leptin
may integrate a complex response pattern via
concerted hypothalamic actions that supervise
diverse pituitary hormone secretory activities
[107–109]. However, in the human, leptin levels
correlate inversely (rather than directly, as in the
rat) with GH axis secretory activity, as illustrated in Fig. 4.7 [55].
a
Older Women
Mean GH Concentration (µg/L)
3
P = 0.0072
r = -0.662
+
+
2
+
+
1
+
+
+
0
+ +
++
+
+
5
0
+
10
+
20
15
Leptin (ng/mL)
b
Women (fed/fasting)
10
Serum GH Concentration (µg/L)
Fig. 4.7 (a) Inverse
log-linear relationship
between fasting serum
leptin concentrations
and integrated 24-h
serum GH
concentrations in 15
healthy postmenopausal
women [55]. (b) Similar
inverse (exponential)
regression between
serum leptin and GH
output in young women
fed or fasted [58]. P and
r values for the linear
regressions are shown.
Adapted with
permission
The exact metabolic mechanisms that subserve
hypothalamo–pituitary responses to exercise
training are not known. Among those extensively
considered are free fatty acids, which clearly can
inhibit GH secretion [15]. On the other hand, any
direct role of free fatty acids in modifying the
GnRH–LH–gonadal axis is not evident. Similarly,
both insulin and free IGF-1 can inhibit GH secretion directly at the anterior pituitary level and
indirectly via hypothalamic effects under several
conditions in certain species [15].
Moreover, prolonged nutrient and/or glucose
deprivation can arrest puberty in the immature
R = -0.683
P = 0.014
8
6
4
2
0
0
6
12
18
Serum Leptin Concentration (µg/L)
24
30
4
Impact of Chronic Training on Pituitary Hormone Secretion in Humans
sheep and modify hypothalamic peptide secretion (e.g., stimulate CRH and/or AVP, while
inhibiting GnRH, secretion) [104]. In contrast,
carbohydrate ingestion during exercise in one
study in the human seemed to increase cortisol
and decrease gonadotropin release [110], whereas
maintenance of euglycemia in another study
abolished exercise-induced ACTH–cortisol
release in nearly exhaustively exercised volunteers [111]. Finally, as intimated above, the peptide leptin can modify somatostatin, GnRH, TRH,
and NPY gene expression, among other hypothalamic responses to the stress of fasting [55, 58].
Overall, we postulate that such multifactorial
metabolic cues and the sex steroid milieu significantly codetermine neuroendocrine responses to
exercise training [112–114]. In addition, under
the most severe exercise stimulus, overall “finalcommon-pathway” stressor responses may prevail, such as secretion of reproductively inhibitory
CRH and endogenous opioids, with consequent
suppression of GnRH–LH secretion and conversely (in a species-specific manner) stressdriven alterations in the GH–IGF-­1 axis [10, 15,
38, 115–123].
Implications
Among other implications of chronic training are
favorable nonendocrine adaptations of hemodynamic and cardiovascular function. These
changes are likely to be important in long-term
health risk. Moreover, body compositional
changes, motivated in part by the above neuroendocrine alterations, would be predicted to have a
propitious impact on population-wide morbidity
and mortality [12, 117]. In contrast, alterations in
bone density accompanying chronic exercise
have bipotential implications, e.g., with putatively increased fracture risk owing to sex steroid
deprivation (amenorrhea) and possibly reduced
total (height) growth potential [75] and, conversely, variably decreased fracture risk owing to
increased bone density associated with the stress–
strain mechanism of enhanced bone apposition
accompanying sustained physical training [22,
124–126]. However, other confounding factors,
65
such as concurrent estrogen status, activity of the
GH–IGF-1 axis, ethnicity, and gender, can also
modify bone density and fracture risk. For example, we recently observed that black men and
women show increased bone mass over their
Caucasian counterparts but that only in men is
the higher bone density in blacks associated with
correspondingly increased GH secretion [127].
The mechanisms underlying such ethnic differences are also not yet understood, nor are possible ethnic differences in endocrine responsiveness
to exercise stress well investigated.
Summary
The impact of chronic exercise training on the
neuroendocrine control of the anterior pituitary
gland, and its feedback and feedforward inputs, is
complex. Multiple determinants influence adaptive hypothalamo–pituitary secretory responses
to physical stress, namely, training intensity and
duration, including overreaching exercise, concurrent weight loss, diet and energy balance,
other associated stressors (both psychological
and physical), body composition, gender, age, the
sex steroid milieu, and developmental/maturational status. Confounding variables include
interspecies differences, the complexity of neurohormone secretion (pulsatile, circadian, and
entropic rhythms), the difficulty in interpreting
earlier cross-sectional studies (with possible
ascertainment bias) compared to longitudinal
data, and the distinction between biochemical
changes in and clinically significant sequelae of
neurohormonal alterations with exercise. We
emphasize that measurable pituitary responses to
exercise should be viewed as part of a feedforward and feedback control system, as exemplified
for the GH–IGF-1, GnRH–LH, CRH–AVP–
ACTH, and other axes, with yet additional
between-axes interactions. Although the final
metabolic mechanisms that direct neuroendocrine changes in chronic training are not known
definitively (e.g., free fatty acids, insulin, IGF-1,
glucose, sex hormones, leptin, and/or others),
their nature is likely multifactorial. In response to
extremely strenuous exercise, stress-like neuro-
J. D. Veldhuis and K. Yoshida
66
endocrine reactivity may predominate, whereas
with appropriately modulated exercise intensity
and volume, favorable clinical benefits, such as
augmented GH secretion, cardiovascular conditioning, improved sense of well-being, and
­preserved reproductive function and bone density, likely ensue.
Acknowledgments We thank Patsy Craig for her skillful
preparation of the manuscript and Paula P. Azimi for the
data analysis, management, and graphics. This work was
supported in part by NIH Grant MO1 RR00847 (to the
General Clinical Research Center of the University of
Virginia Health Sciences Center), Research Career
Development Award 1-KO4-HD-00634 (to J. D. V.), the
Baxter Healthcare Corporation (Round Lake, IL, to J. D.
V.), the NIH-supported Clinfo Data Reduction Systems,
the University of Virginia Pratt Foundation and Academic
Enhancement Program, the National Science Foundation
Center for Biological Timing (Grant DIR89-20162), and
the NIH NICHD U54 Center for Reproduction Research
(HD96008).
9.
10.
11.
12.
13.
14.
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5
Exercise and the GH-IGF-I Axis
Alon Eliakim and Dan Nemet
Introduction
Physical activity and exercise play an important
role in tissue anabolism, growth, and development, but the mechanisms that link patterns of
physical activity with tissue anabolism are not
completely understood. The anabolic effects of
exercise are not limited to participants in competitive sports since substantial anabolic stimulus arises even from relatively modest physical
activities [1].
The exercise-associated anabolic effects are
age and maturity dependent. Naturally occurring levels of physical activity are significantly
higher during childhood, and during adolescence there is a simultaneous substantial
increase in muscle mass and strength. Thus,
the combination of rapid growth, high levels of
physical activity, and spontaneous pubertyrelated increases in anabolic hormones (growth
hormone [GH], insulin-­
like growth factor-I
[IGF-I], and sex steroids) suggests the possi-
A. Eliakim (*)
Endocrinology Clinic, Meir Medical Center, Sackler
School of Medicine, Tel Aviv University, Department
of Pediatrics, Kfar Saba, Israel
e-mail: eliakim.alon@clalit.org.il
D. Nemet
Child Health and Sports Center, Meir Medical Center,
Sackler School of Medicine, Tel Aviv University,
Department of Pediatrics, Kfar Saba, Israel
bility of integrated mechanisms relating exercise with anabolic responses. In contrast,
participation of young athletes in intense competitive training, especially if associated with
inadequate caloric intake, may be associated
with health hazards and may reduce growth
potential [2].
Training efficiency depends on the exercise
intensity, volume, duration, and frequency and on
the athlete’s ability to tolerate it. An imbalance
between the training load and the individual’s tolerance may result in under- or overtraining.
Therefore, efforts are made to develop objective
methods to quantify the fine balance between
training load and the athlete’s tolerance. The
endocrine system, by modulation of anabolic and
catabolic processes, seems to play an important
role in the physiological adaptation to exercise
training [3]. In recent years changes in circulating components of the GH-IGF-I axis, a system
of growth mediators that control somatic and tissue growth [4], have been used to quantify the
effects of training [5]. Interestingly, exercise is
also associated with remarkable changes in catabolic hormones and inflammatory cytokines [i.e.,
interleukin-6 (IL-6)], and the exercise-related
response of these markers can be also used to
gauge exercise load [6, 7]. Anabolic response
dominance will eventually lead to increased muscle mass and improved fitness, while prolonged
dominance of the catabolic response, particularly
if combined with inadequate nutrition, may
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_5
71
72
ultimately lead to overtraining. Therefore, the
­evaluation of changes in these antagonistic circulating mediators may assist in quantifying the
effects of different types of single and prolonged
exercise training and recovery modalities.
This chapter demonstrates the effects of exercise on the GH-IGF-I axis, with an emphasis on
the unique relationships between the exercise-­
related anabolic response and exercise-associated
changes in inflammatory mediators. An important goal of this chapter is to show how exercise-­
induced changes in the GH-IGF-I-inflammatory
axis can be used by elite athletes and their accompanying staff to evaluate training load throughout
the competitive season and in the preparation for
competition in “a real-life” setting. Finally, the
chapter demonstrates new data on the possible
use GH-IGF-I genetics in sports selection and
prediction of excellence.
A. Eliakim and D. Nemet
paracrine secretion and regulation, which are
only partially GH dependent. IGF-I is responsible for most, but not all, anabolic and growth-­
related effects of GH. IGF-I stimulates SMS
secretion and inhibits GH by a negative feedback
mechanism [9].
The bulk of circulating IGF-I is bound to
IGFBPs. The most important circulating BP is
IGFBP-3, which accounts for 80% of all IGF
binding. Some IGFBPs are GH dependent (e.g.,
IGFBP-3), while others (IGFBP-1 and IGFBP-2)
are insulin dependent (being high when insulin
level is low). The interaction between IGF-I and
its BPs is even more complicated since some BPs
stimulate (e.g., IGFBP-5), while others inhibit
(e.g., IGFBP-4) IGF-I anabolic effects [10].
Some hormones in the GH-IGF-I axis (i.e.,
GHRH and GH) have a pulsatile secretion pattern, and it has been shown that GH pulsatility is
important for growth rate acceleration [11]. In
contrast, IGF-I and IGFBPs level are relatively
stable throughout the day.
The GH-IGF-I Axis
Furthermore, several components of the axis
The GH-IGF-I axis is composed of hormones, are age and maturity dependent. GH, GHBP,
growth factors, binding proteins (BP), and recep- IGF-I, and IGFBP-3 reach their peak levels durtors that regulate essential life processes. The ing puberty [12] and decrease with aging [13].
axis starts at the central nervous system where These changes are partially sex hormone mediseveral neurotransmitters (e.g., catecholamines, ated. Nutritional status influences the GH-IGF-I
serotonin, cholinergic agents, etc.) stimulate the axis as well. Prolonged fasting and malnutrition
hypothalamus to synthesize growth hormone-­ increase GH secretion, yet despite elevated GH,
releasing hormone (GHRH) and somatostatin IGF-I levels remain low due to reduced levels of
(SMS). GHRH stimulates the anterior pituitary to GH receptors [14]. All these factors must be
taken into account when studying the effect of
secrete GH, while SMS inhibits GH secretion.
GH is the major product of the axis. One of exercise on the GH-IGF-I axis.
GH most important functions is the stimulation
of hepatic IGF-I synthesis. However, some GH
effects on metabolism, body composition, and Optimizing Training Modalities
tissue differentiation are IGF-I independent.
Tissue GH bioactivity results from interaction Aerobic Training
between GH and its receptor. The GH receptor is
composed of intra- and extracellular transmem- The majority of the current knowledge regarding
brane domains. The extracellular domain is iden- the importance of the GH response to exercise is
tical in structure to GH-binding protein (GHBP) based on studies examining the effect of aerobic-­
[8]; thus, measuring circulating GHBP levels type exercise in individualized sports [15, 16]. To
this end, when exercise is performed at the same
reflects GH receptor number and activity.
IGF-I is one of the insulin-related peptides. absolute intensity, the GH response is greater in
Some of IGF-I effects are GH dependent, but the less fit subjects [17]. Yet, when subjects perform
majority of its actions occur due to autocrine or exercise at the same absolute, rather than relative
5
Exercise and the GH-IGF-I Axis
intensity, some individuals exercise below, while
others exercise above, their lactic/anaerobic threshold (LAT). This is important since circulating GH
levels increase only in response to aerobic exercise
intensity above the LAT and because exercise loads
of 75–90% of the maximal aerobic power yielded
greater GH increase than milder loads. Therefore,
results of studies in which the GH response to
exercise was tested at an absolute work rate demonstrate simply that as individuals become fitter,
the stress associated with exercise at an absolute
work rate is reduced. The obvious implication for
athletes is that as they become more physically fit,
a more intense exercise should be performed to
stimulate GH secretion. This is consistent with the
common coaching modality of training cycles
with workloads of increased intensity throughout
the training season.
The duration of aerobic exercise for the stimulation of GH secretion should be at least 10 min
[18]. The exercise-induced GH peak occurs
25–30 min after the start of exercise (slightly earlier in females compared to males), irrespective
to its duration [19, 20]. Thus, when the exercise
task is brief (e.g., 10 min), GH peak is reached
after the cessation of exercise, while, when exercise is long (e.g., 60 min), GH peak is reached
while the individual is still exercising. The important possible implication for athletes is that brief
training sessions can be enough to stimulate the
GH-IGF-I axis and to achieve a “training effect”
(i.e., relative to this hormone and its response).
Pituitary refractoriness, a time in which the
normal pituitary gland will not respond sufficiently to any stimulus for GH release, could also
influence the GH response to exercise. For example, the GH response to exercise was inhibited if
a spontaneous, early morning, GH pulse had
occurred within 1 hour prior to the exercise test
[20]. A refractory period of at least 1 hour was
also shown following exercise-induced GH
secretion (i.e., the subsequent GH response to
exercise was attenuated) [21]. GH auto-­inhibition,
exercise-induced elevation in free fatty acids, or
alterations in parasympathetic-sympathetic tone
can explain the development of pituitary refractoriness. A recovery from pituitary refractoriness to
GH secretion was seen if a second bout of high-­
73
intensity endurance exercise was performed
3 hours after the first session [22]. Consistent
with this report, integrated 1.5 hours GH concentrations were significantly greater if differences
between the exercise bouts (30 min, 70% VO2
max [maximal oxygen uptake]) were 3.5 hours
and not when 1 hour apart [23]. The practical
application for athletes should therefore be that
in order to achieve optimal GH secretion, the rest
interval between multiple daily training sessions
should be long enough (probably more than
3 hours) to allow pituitary recovery.
Anaerobic Exercise
A major progress was achieved in recent years in
the understanding of the effects of anaerobic
exercise on the GH-IGF-I axis. Stokes et al. [24]
studied the effect of a single supramaximal 30 sec
sprint on a cycle ergometer against different levels of resistance workloads. They found that the
increase in GH levels was significantly greater
when resistance was 7% (faster cycling) and not
9% (slower cycling) of body mass. Consistent
with that, it was shown that when heavier loads
were lifted, more total work was performed, and
higher IGF-I levels were found using faster compared to slower tempo resistance training [25].
The possible implication for athletes is that lower
levels of resistance and/or faster anaerobic efforts
may better stimulate the GH-IGF-I axis and thus
preferred by coaches and athletes.
Interval training is currently one of the most
frequent training methods used in anaerobic
and aerobic-type sports [26]. The intensity of
such training depends on the running distance
(sprint versus long distance), running speed
(percent of maximal speed), the number of repetitions, and the length of the rest interval
between the runs. In addition, coaches and athletes often change the style of the interval
training and use constant running distances
(e.g., 6 × 200m), increasing distance interval
session (e.g., 100 m–200 m–300 m–400 m),
decreasing distance interval session (e.g.,
400 m–300 m–200 m–100 m), or a combination
of increasing-decreasing distance interval session
A. Eliakim and D. Nemet
74
(e.g., 100 m–200 m–300 m–200 m–100 m).
While these style differences may seem negligible, they may involve different physiological
demands, since in the increasing distance protocol, metabolic demands (e.g., lactate levels)
increase gradually and are highest toward the
end of the session, while in the decreasing distance protocol, the metabolic demands are
higher from the beginning of the session [27], if
the intensity of the intervals is appropriate and
able to be maintained by the athlete.
A significant increase in GH and IL-6 levels
was demonstrated following a typical constant
distance (4 × 250m) interval training [28].
Consistent with previous findings in aerobic
exercise, changes in the GH-IGF-I axis following
the brief sprint interval exercise suggested
exercise-­
related anabolic adaptations. The
increase in IL-6 probably indicates its important
role in muscle tissue repair following anaerobic
exercise [29]. It was suggested that changes in
the anabolic/catabolic/inflammatory balance can
be used as an objective tool to gauge the training
intensity of different types of anaerobic exercises
and training periods as well.
More recently, we evaluated the effect of
increasing (100–200–300–400 m) and decreasing distance (400–300–200–100 m) sprint interval training protocols, two other common types
Decreasing
12
of sprint interval training, on the balance
between anabolic, catabolic, and inflammatory
mediators [27]. Both types of sprint interval
trainings led to a significant increase in lactate
and the anabolic factors GH and IGF-I. Both
types of sprint interval sessions led to a significant increase in the circulating inflammatory
mediators (IL-6). Interestingly, the lactate and
GH area under the curve was significantly
greater in the decreasing distance session. In
contrast, rate of perceived exertion (RPE) was
higher in the increasing distance session. Thus,
despite similar running distance, running speed,
and total resting period in the two interval training sessions, the decreasing distance interval
was associated with a greater metabolic (lactate)
and anabolic (GH) response (see Fig. 5.1).
Interestingly, these greater metabolic and anabolic responses were not accompanied by an
increase in RPE suggesting that physiological
and psychological responses to interval training
do not necessarily correlate. When the athletes
were asked to explain why the increasing distance protocol was perceived as more intense,
they replied that the fact that the longest and
hardest run (400 m) was only at the end of the
session was very difficult to tolerate. Coaches
and athletes should be aware of these differences and, as a consequence, of the need for
Increasing
40
10
30
8
6
20
4
10
2
0
Growth hormone (ng/ml)
0
Fig. 5.1 The effect of decreasing and increasing distance
of sprint interval exercise on GH and GH area under the
curve responses. The decreasing distance interval was
Growth hormone AUC (ng\ml)
associated with a greater anabolic [GH (left) and GH AUC
(right)] response
5
Exercise and the GH-IGF-I Axis
specific recovery adaptations after different
types of interval training sessions. Differences
in physiological and psychological responses to
competitive sport training, and their influence
on the training course and recovery process,
should also be better addressed in future
research work.
Finally, in contrast to the observation that both
aerobic and anaerobic exercise require a high
metabolic demand in order to stimulate GH
secretion, we previously demonstrated a small
but significant GH response to an exercise input
that was perceived as difficult by the participants
(i.e., 10 min of unilateral wrist flexion, a small
and relatively unused muscle group) but which
had no effect on heart rate or circulating lactate
levels [30, 31]. This suggests that factors like the
individual’s perceived exertion and associated
psychological stress play an important role in the
activation of the hypothalamic-pituitary axis and
to GH release even in exercise protocols involving small muscle groups.
Resistance Exercise
Previous studies have demonstrated increases in
GH following a session of resistance exercise in
adolescent and prepubertal boys. Children and
adolescents demonstrate a lower GH response
to resistance exercise compared with adults,
presumably due to higher baseline GH levels
[32]. As mentioned before, growth hormone is
secreted in a pulsatile manner, with highest
secretion during deep sleep, especially in children. Interestingly, Nindl et al. [33] reported
that in men, an afternoon resistance training session affected the GH secretion pattern during
resting states. Specifically, while mean GH
secretion did not change, a lower rate of secretion in the first half of sleep and a higher rate of
secretion in the second half of sleep were
detected. This could be a direct effect of the
resistance exercise on GH secretion, or an indirect effect on sleep quality. Considering the
importance of nighttime GH secretion for linear
growth, resistance training in adolescent athletes during different times of day (e.g., morn-
75
ing vs afternoon) may have different effects on
sleep quality and/or directly on GH secretion
pattern. Likewise, effects on the pulsatile secretion pattern may potentially even have effects on
their linear growth. There is certainly a need for
further research in this area.
Team Sports
Very few studies examined the effect of exercise
on the GH-IGF-I axis in team sports. We previously demonstrated an increase in GH, testosterone, and IL-6 levels following a typical volleyball
practice in adolescent national team level male
and female players [34]. Interestingly, one of our
most important findings was the effect of training
on the endocrine response to a single practice.
The hormonal response to a typical 60 min volleyball practice was assessed before and after 7
weeks of training during the initial phase of the
season in elite national team level male and
female players. In male players [35], training
resulted in significantly greater GH increase
along with significantly reduced IL-6 response to
the same relative intensity volleyball practice. In
female players [36], training resulted in significantly lower cortisol and IL-6 increase to the
same relative intensity volleyball practice. The
results suggest that along with the training-­
associated improvement of power, anaerobic and
aerobic characteristics, part of the adaptation to
training is that a single practice becomes more
anabolic and less catabolic/inflammatory as
training progresses during the initial phases of
the training season (Fig. 5.2). Hormonal measurements therefore may assist athletes and their
coaching staff in assessing the training program
adaptation throughout different stages of the
competitive season.
Finally, higher social position was associated
with higher levels of IGF-I in both men and
women, independent of wide range of known
confounders such as age, ethnicity, body weight,
and nutrition [37]. Along this line, Bogin et al.
[38] studied high-level male and female competitive athletes from different university team sports
(men, lacrosse, handball, rugby, and volleyball;
A. Eliakim and D. Nemet
76
5
Lactate nmol/L
4
3
2
1
0
2.5
Pre training
IL-6 pg/ml
2.0
Post training
1.5
1.0
.5
0.0
Fig. 5.2 The effect of training on the hormonal response
to a single volleyball practice in male adolescent players.
Same level of training (i.e., lactate response) leads to a
reduced inflammatory response (IL-6)
Fig. 5.3 A proposed
exercise-training-IGF-I
cycle. With proper
training, both single
practice and prolonged
training increase IGF-I
levels, which in turn
may increase the
chances of an athlete to
win
women, football, rugby, netball, and volleyball)
and assumed that what determines the social
position in this social network is the level of
­success in sports (and not the economic status).
Therefore the athletes were divided into winners
and losers. The main finding of the study was that
both pre- and post-competition IGF-I levels were
about 11% greater among winners. There was no
difference in the competition-related changes in
IGF-I levels between the groups, suggesting that
it is the baseline levels of IGF-I and not the
change in IGF-I levels during the competition
that may contribute to winning. This is the first
study that related IGF-I levels with winning. It
seems that IGF-I levels integrate the multiple
genetic, nutritional, social, and emotional influences to a coherent signal that regulates growth
and possibly athletic performance. This suggests
a novel cycle: both single practice and prolonged
training increase IGF-I levels, which in turn
increase the chances of an athlete to win (see proposed model in Fig. 5.3). However, future larger
studies that analyze other types of team sports
and individual sports and that provide better control for nutritional, training, and doping status are
needed to confirm this very interesting finding.
Single practice
IGF Polymorphism
ul
e
f
ss
c
uc
S
Prolonged
training
N
on
su
cc
es
sf
ul
IGF-I
IGF-I
Winning
Losing
5
Exercise and the GH-IGF-I Axis
“Real-Life” Exercise Studies
The majority of studies on the effect of exercise
on the GH-IGF-I axis are laboratory-based. There
is no doubt that laboratory-based science is
important for understanding the exercise-related
endocrine response. However, the translation of
this knowledge to everyday use of competitive
athletes is complicated, and there is a severe lack
of “real-life” setting studies on the endocrine
effect of exercise training. One of the main obstacles of executing “real-life” training studies is
exercise standardization. We recently compared
previous reports on the effect of “real-life” typical field individual (i.e., cross-country running
and wrestling – representing combat versus noncombat sports) and team sports practice (i.e., volleyball and water polo – representing water and
land team sports) on GH levels [39]. In this study,
we were unable to control for the participants’
fitness level or for each practice’s intensity. In
order to achieve some standardization, however,
participants did not train during the day before
the study, the duration of each practice was limited to 60–90 min, and the practice was performed during the initial phases of the training
season when athletes are in relatively lower fitness level. All practice sessions were performed
in the morning hours, and each typical practice
included warm-up, main training segment, and
cooldown. Blood samples were collected immediately before and at the end of practice, and the
effect of the typical practice on hormonal and
cytokine levels was expressed as percent change.
Despite some limitations within the study, several important observations and conclusions
could be drawn about the “real-life” training-­
related GH response from this unique comparison. These include the following: (1)
cross-country running practice and volleyball
practice in both males and females were associated with significant increases of GH, (2) the
magnitude (percent change) of the GH response
to the different ­practices was determined mainly
by what were the pre-exercise GH levels, (3)
there was no difference in the GH response
77
between individual and team sports practices,
and (4) interestingly, the GH response to the typical practices was not influenced by the practiceassociated lactate change.
Cryotherapy, Recovery,
and the GH-IGF-I Axis
The development of methods to enhance the
recovery of elite athletes from intense training
and/or competition has been a major target of
athletes and their accompanying staff for many
years. Cryotherapy is widely used to treat sports-­
associated traumatic injuries and as a recovery
modality following training and competition that
may cause some level of traumatic muscle injury
[40, 41]. However, evidence regarding the effectiveness and appropriate guidelines for the use of
cryotherapy are limited. To this end, Nemet et al.
studied the effect of cold ice pack application following a brief sprint interval training on the balance between anabolic, catabolic, and circulating
pro- and anti-inflammatory cytokines evaluated
in 12 male, elite junior handball players [42]. The
interval practice (4 × 250m) was associated with
a significant increase in GH and IL-6 levels.
Local cold-pack application was associated with
significant decreases in the anabolic factors IGF-I
and IGF-binding protein-3 during the recovery
from exercise, supporting some clinical evidence
of possible negative effects of cryotherapy on
hormonal responses. These results, along with no
clear detected effect on muscle damage or
delayed onset muscle soreness (DOMS), may
suggest that the use of cold packs should probably be reserved for traumatic injuries or used in
combination with active recovery and not with
complete rest. However, the findings of this study
illustrate how exercise-induced changes in the
GH-IGF-I axis and other catabolic and inflammatory markers may be used as an aid in competitive training. Further studies are needed to
explore the beneficial use of anabolic, catabolic,
and inflammatory markers measurement in the
“monitoring” of recovery from exercise.
78
Nutrition, Performance,
and the GH-IGF-I Axis
Nutritional factors may intervene with the GH
response to exercise. For example, intravenous
administration of the amino acid arginine is a
strong stimulator of GH release and therefore
used, for example, as one of the more common
provocation tests for GH secretion in the diagnosis of some clinical states (e.g., short stature).
Recently, it was demonstrated that oral arginine
stimulates GH secretion as well [43]. Therefore,
it is possible that the ingestion of arginine prior to
exercise may attenuate the exercise-related GH
response, most probably due to induction of a
refractory period [44]. Along these lines, ingestion of a lipid-rich meal 45–60 min prior to an
intermittent 30 min cycle ergometer exercise
resulted in a significant more than 40% reduction
in the exercise-induced GH elevation in healthy
children [45]. The effect of prior high-fat meal
ingestion appeared to be GH selective, as other
counter-regulatory hormone responses to exercise, such as glucagon, cortisol, and epinephrine,
were not affected. Similarly, administration of
high-fat meal attenuated the magnitude of GH
response to exercise also in adults, and this inhibition was correlated with circulating levels of
SMS [46]. Interestingly, a high carbohydrate
meal with a similar caloric content was also associated with a small decrease in GH response to
exercise; however, this decrease was not statistically significant. These studies indicate that food
consumption prior to exercise or sporting practice should be carefully selected, since a consumption of high-fat meal may affect the
hormonal response to a training session.
Very few studies have examined the effects
of nutrition on longer periods of training (i.e.,
weeks or months) primarily due to logistical
issues. The timing of nutritional supplementation may also affect the training-associated
response of the GH-IGF-I axis. For example,
the combination of post-exercise essential
amino acids and carbohydrate supplementation
was accompanied by significant increases in
free IGF-I during 3 weeks of high-intensity
interval training [47] (compared to carbohy-
A. Eliakim and D. Nemet
drate only or placebo). Protein supplementation
1 hour before and after practice during 10 weeks
of resistance training (four times/week) were
more effective than carbohydrate placebo in
increasing muscle mass and muscle strength
and were associated with greater increases in
IGF-I and IGF-I mRNA in untrained males
[48]. Consistent with these findings, twice daily
protein compared to carbohydrate supplementation during 6 months of strength and conditioning training (five times/week) was
associated with greater increase in IGF-I levels
in untrained late pubertal and young adult
males and females [49]. These results as well as
others suggest a beneficial effect for protein
supplementation during prolonged period of
resistance training, but more research is needed
on this topic to provide specific amount and
type of protein supplementation.
Amenorrhea, Performance,
and the GH-IGF-I Axis
The inhibitory effect of exercise training, in particular, when associated with nutritional deprivation, on the pulsatile release of hypothalamic
GnRH and pituitary LH and FSH secretion is
well established and will be discussed in more
detail in other chapters of this book (see Chaps.
4, 7, and 8). This inhibition results in increased
risk of athletic amenorrhea and hypoestrogenism
[50]. To this end, it was shown that the exercise-­
associated GH release is attenuated in amenorrheic athletes. The mechanism for the attenuated
amenorrhea-associated exercise-induced GH
response is not completely understood. However,
it was found recently [51] that low estrogen leads
to decreased post-exercise type 1 deiodinase (an
enzyme that converts T4 to the more active thyroid hormone T3), reduced T3 levels, and in turn
a blunted GH response. This is particularly relevant to the adolescent female athlete, since the
prevalence of amenorrhea among these athletes
is 4–20 times higher than the general population
[52]. “Athletic amenorrhea” appears mainly in
younger athletes and is associated with sports
activities where leanness provides a competitive
5
Exercise and the GH-IGF-I Axis
79
advantage (e.g., aesthetic-type sports, long-­
distance running, etc.) and, in particular, where
intense training is accompanied by inadequate
nutrition [50].The reduced exercise-induced GH
response in these athletes should be considered
critically important since it indicates probably
reduced training effectiveness and performance.
Consistent with that Vanheest et al. [53] showed
that reduced energy intake and availability that
was associated with ovarian suppression was
also accompanied by lower T3 and IGF-I levels
and by a 9.8% decline in 400 m swim velocity
compared to 8.2% improvement among female
swimmers without ovarian suppression at the
end of 12 weeks of training (N.B., in total, 18%
difference!). This occurred despite similar training protocols and while the ovarian suppressed
swimmers were still menstruating (although less
regularly). This is important because some
coaches and young athletes promote energy-­
restrictive practices with the belief that it
improves competitive performance [54]. The
results of this study emphasize that athletes can
maintain chronic energy deficit for varied periods with continued success in sport; however,
prolonged negative energy balance results in
training maladaptation and reduced performance. This may be particularly relevant for athletes during adolescence, a time with greater
energy needs for growth and maturation.
Measurements of hormones and in particular
IGF-I levels can also assist athletes and coaches
in the training preparation for selected competitions. For example, in one study, the effect of
4 weeks of training on fitness, self-assessment
physical conditioning scores, and circulating
IGF-I were determined in elite professional
handball players [55] during their preparation for
the junior world championships. Training consisted of 2 weeks of intense training followed by
2 weeks of relative tapering. Circulating IGF-I
and physical conditioning scores decreased initially and returned to baseline levels at the end of
tapering. There was a significant positive correlation between the changes in circulating IGF-I and
self-assessed physical conditioning scores suggesting that the player’s self-assessment may be a
somewhat reliable tool when laboratory assessment is unavailable (see Fig. 5.4). Consistent
with these findings, a follow-up of IGF-I levels
during a training season in elite adolescent wrestlers showed an initial decrease in IGF-I level
during periods of heavy training and return to
baseline during tapering down and prior to the
competition season [56]. Interestingly, changes
in the pro-inflammatory mediators IL-6 correlated negatively with changes in IGF-I, being
high when IGF-I level was low, and normalized
∆ Change in self assessment physical conditioning scores
50
∆ Change in circulating IGF-I (ng/ml)
Fig. 5.4 Relationship
between changes in
self-assessment physical
conditioning scores and
change in circulating
IGF-I during 2 weeks of
intense training in
handball players. There
was a significant
correlation between
self-assessment scores
and change in
circulating IGF-I
Preparation for Competition
0
–4
–50
–100
–150
–200
–250
r=0.85
–3
–2
–1
80
when IGF-I levels normalized, emphasizing their
potential contributing role for the training-­
associated change in IGF-I.
Tapering training intensity prior to the competition is a well-known training methodology used
to help the athlete to achieve their best performance (i.e., increased rest leading to a psychophysiological restoration) [57]. Interestingly, this
strategy is indeed associated with a parallel
increase in circulating IGF-I levels. Therefore,
measurements of IGF-I may assist coaches and
athletes in their training preparations and provide
a clue whether the tapering is being effective.
Interestingly, in sports that do not plan their training for a specific targeted date of peak performance, like many of the team sports that train in
the same relative intensity throughout a regular
season (e.g., handball, soccer, etc.), changes in
IGF-I level and its major binding protein
IGFBP-3 are not typically found [58].
In optimal conditions, during the tapering of
training intensity, IGF-I level will increase above
baseline levels and will be associated with
improved performance; however, this does not
occur always. Since IGF-I can be reduced by
nutritional imbalance and weight loss, it is possible that a deliberate decrease in body weight in
athletes who participate in weight category sports
(e.g., judo, wrestling), or even in team sport players prior to major tournaments, may prevent further increase in this anabolic hormone and will be
associated “only” with a significant return to
baseline values [56, 59]. This emphasizes the
importance of proper nutritional counseling all
throughout the training season. Previous studies
demonstrated in athletes a training-associated
negative correlation between circulating IGF-I
and ghrelin, a hormone that is secreted by the
stomach and pancreas and known to stimulate
hunger [60]. Moreover, decreases of ghrelin and
leptin, both known to mediate energy balance,
were found following a 3-month preseason
­preparatory training in young female handball
and basketball players [61]. All together this suggests that hormonal relationships, as one would
expect, play a mediating role in training-induced
associated energy balance, appetite, body composition, and muscle performance changes.
A. Eliakim and D. Nemet
Interestingly, despite decreases in circulating
IGF-I during period of intense training, physical
fitness may still improve, as muscle mass does
[62–65]. This suggests that while changes in circulating IGF-I are good markers of the general
condition and energy balance of the athlete, they
are not necessarily good indicators of the athlete’s performance level. Probably, it is the local
muscle levels of these hormones, and their autocrine or paracrine secretion, that are or could be
more indicative of skeletal muscle performance
[66, 67]. Nonetheless, tapering of the training
intensity, was found to be associated with
both increased IGF-I level and with further
improvement of exercise performance of the athletes [57, 68].
It is still unknown what should be the below
baseline permitted decrease of IGF-I levels during
periods of heavy training, or what should be the
optimal increase of this substance during periods
of tapering and reduced training intensity (i.e.,
what magnitude of change is detrimental versus
beneficial). However, the inability to increase circulating IGF-I levels before the target competition
may suggest inappropriate recovery and suggest
to the athlete and his/her coach that the athlete’s
general condition is not optimal. Collection of
baseline and training-related hormonal changes,
with a comparison to the hormonal response in
previous seasons, and the knowledge and experience of the past success may prove to be of a very
significant relevance as well.
I GF-I Genetics, Sports Selection,
and Sports Excellence
The potential use of genetic single nucleotide
polymorphisms (SNPs) of hormone genes, as a
tool to assist in predicting future athletic performance, is currently an extremely challenging
topic, mainly because each possible gene makes
only a small contribution to the overall heritability. The majority of previous reports of hormonal gene polymorphism and athletic
performance in professional athletes studied
variations in the IGF-I polymorphism. The
polymorphism of IGF-I promoter frequency
Exercise and the GH-IGF-I Axis
AA
AG
GG
100
80
60
40
20
ift
W
ei
gh
tl
um
t/J
in
Sp
r
ur
an
ce
p
0
En
d
was significantly greater in athletes (9.2%)
compared to controls (2.4%) and in particular
among strength (11%) compared to athletes participating in team sports (7.8%) [69]. Our
research group previously demonstrated [70] a
higher frequency of the IGF-­IC1245T T/T IGF-I
promoter polymorphism among Israeli athletes
(4.8%), compared to controls (nonexistence).
Interestingly, while T/T polymorphism carriers
were both endurance and power athletes, endurance athletes were of a national level, but the
power athletes were top-­level international and
Olympic athletes. This suggests that the IGF1
T/T polymorphism may be more beneficial for
power sports performance at the elite level.
Along these lines, we also recently assessed
[71] the frequency of another polymorphism of
the IGF-I gene (i.e., IGF-­Irs7136446) and demonstrated that the frequency of carrying the GG
genotype was significantly greater among
sprinters compared to weight lifters (see findings depicted in Fig. 5.5). Taken all together,
this may suggest that among certain power
sports activities, the IGF-I polymorphism is
more important for speed rather than strength.
In addition, we showed that the IGF2 (rs680)
GG genotype frequency was significantly
greater among sprinters compared to weight lifters [72], suggesting that carrying this IGF2
polymorphism may also be beneficial mainly
for speed-related and not for strength sports.
Circulating IGF2 levels were lower among individuals homozygous for the G allele [73], and
higher levels of plasma IGF-I were found in
individuals carrying the IGF2 GG genotype
[74]. It is possible that the beneficial effect of
the IGF2 rs680 polymorphism on speed performance is not necessarily mediated through its
influence on circulating IGF2, but via its effect
on IGF-I levels. This point, however, needs
much further investigation.
Interestingly, it has been previously demonstrated that in contrast to elite track and field athletes, single nucleotide polymorphisms of IGF1,
IGF1 receptor, and IGF2 were not frequent
among swimmers [72, 75, 76]. These results possibly suggest that the insulin-like growth factor
system is less significant for elite swimming than
81
% prevalence
5
Fig. 5.5 The prevalence of the A/G IGF-I rs7136446
polymorphism among national and top-level Israeli endurance athletes, short-distance runners/jumpers and among
weight lifters (p = 0.036, for GG genotype frequency,
sprinters vs weight lifters)
for running performance. The mechanism for this
discrepancy is currently unknown and in need of
study. A possible explanation is that swimming
excellence is mainly affected by the swimmer’s
physical attributes (particularly limb length) and
swimming technique [77], possibly masking
physiologic, metabolic, and muscle mass differences and enabling tall and technically skilled
swimmers to excel in the majority of swimming
distances.
These results indicate that extreme caution
should be done before pooling different types
of sport in genetic research because despite
seemingly similar metabolic characteristics,
­
athletes from different sport disciplines carry
­
different genetic polymorphisms. Whether a multipotent athlete who wants to develop a competitive career and carries a beneficial IGF system
polymorphism should prefer track and field over
swimming is currently speculative and hence
must be interpreted with caution. Moreover, one
should always keep in mind that while a favorable genetic predisposition is essential, psychological features and environmental aspects,
including training equipment and facilities, nutrition, familial support, and motivational issues,
are also critically essential for top-level sports
performance success.
82
Summary
In recent years there has been a significant
research progress in the field of exercise endocrinology. It is now clear that monitoring changes in
the balance of anabolic (GH→IGF-I system) and
catabolic hormones and related inflammatory
mediators following different types of exercise
training and during different stages of the training season may help elite athletes and their
coaching staff in developing a more “optimal”
training program and in the preparation for competition. In addition, the use of hormonal genetic
polymorphisms may serve as an additional assisting tool for talent identification and sports selection and perhaps also for building effective (i.e.,
more precise) training programs for athletes.
Further research is needed, however, to better
clarify the complex relationship of training, hormonal responses, nutrition, genetics, and optimal
athletic performance in competitive sports.
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6
Exercise and Thyroid Function
Dorina Ylli, Joanna Klubo-Gwiezdzinska,
and Leonard Wartofsky
Introduction
Thyroid hormone receptors are present in virtually every tissue in the body, thereby permitting
an important physiologic role for the two thyroid
hormones, thyroxine (T4) and triiodothyronine
(T3). Skeletal and cardiac muscle function, pulmonary performance, metabolism, and the neurophysiologic axis are only a few of the important
areas affected by thyroid hormone level [1]. Any
abnormality in thyroid function causing either an
excess or deficiency in circulating thyroid hormone levels can lead to changes in body function
at rest and during exercise. The presence of thyroid
disease can have a major impact on exercise tolerance resulting in reduced performance of strenuous
activities. On the other hand, exercise itself may
have direct or indirect effects on thyroid function,
either secondary to acute alterations in the integ-
D. Ylli
MedStar Health Research Institute, Thyroid Cancer
Research Center, Washington, DC, USA
J. Klubo-Gwiezdzinska
National Institutes of Health, National Institute of
Diabetes and Digestive and Kidney Disease/
Metabolic Disease Branch, Bethesda, MD, USA
L. Wartofsky (*)
Thyroid Cancer Research, Georgetown University
School of Medicine, MedStar Health Research
Institute, Department of Endocrinology,
Washington, DC, USA
e-mail: leonard.wartofsky@medstar.net
rity of the pituitary thyroid axis or to more longlasting changes. In well-trained athletes, alterations
in thyroid function can be viewed as an adaptive
mechanism associated with enhanced performance possibly serving to provide a better balance
between energy consumption and expenditure.
Underlying energy balance does appear to play
an important role in the effects that exercise may
have on the hypothalamus–pituitary–thyroid axis.
Reports in the literature indicate that athletes with
excessive weight loss may exhibit a “low T3 syndrome” accompanied by amenorrhea (in women)
as well as other alterations in pituitary function [2].
Fortunately, thyroid diseases usually can be treated
effectively, and most individuals with thyroid disorders should expect to obtain resolution of their
thyroid-related symptoms, including those associated with a negative impact on their exercise tolerance. The track athlete, Gail Devers, who has been
very public about her experience with Graves’ disease, is a well-known sprinter who went on to win
Olympic fame following treatment for her Graves’
disease and may act as a case in point.
After a brief overview of normal thyroid physiology, this chapter will provide a survey of the
literature describing effects of abnormal thyroid
hormone levels on exercise tolerance, with a special focus on alterations in cardiac, muscle, and
respiratory function. The chapter will conclude
with a review of existing data on the response of
the pituitary–thyroid axis to varying levels and
types of exercise.
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_6
85
D. Ylli et al.
86
Thyroid Physiology
All steps in thyroid hormone (TH) biosynthesis
are driven by thyrotropin (TSH) and are intimately linked to iodine metabolism. Dietary
iodine is reduced to iodide, is absorbed by the
small intestine, and then enters the circulation.
Iodide “trapped” by the thyroid gland subsequently undergoes oxidation by thyroid peroxidase (TPO), iodinating tyrosyl residues in the
storage protein, thyroglobulin, to form the iodothyronines, monoiodotyrosine (MIT), and diiodotyrosine (DIT). MIT and DIT molecules can
then couple to form either tetraiodothyronine
(T4) or triiodothyronine (T3), which are the two
major thyroid hormones. T4 and T3 are bound
within thyroglobulin and stored in thyroid follicles. Under control of TSH, thyroglobulin
undergoes endocytosis and proteolytic digestion,
releasing T4 and T3 into the circulation. The
feedback loop is completed at the hypothalamic
level where declining levels of circulating T4 or
T3 will prompt secretion of thyrotropin-releasing
hormone (TRH), which stimulates synthesis and
secretion of TSH. After binding to its specific
receptor on the thyroid cell membrane, TSH
leads to stimulation of T4 and T3 production.
Only 20% of circulating T3 is derived from thyroid secretion, whereas 80% is derived from the
monodeiodination of T4 by 5′-deiodinase (type
I and type II) in the periphery (see Fig. 6.1) [3].
Since T3 is some 10–15 times more biologically
potent than T4, this latter conversion has been
termed the “activating” pathway of thyroid hormone metabolism. Alternatively, in certain physiologic and pathologic states, the deiodination of
T4 proceeds via a 5-deiodinase (type I and type
III), which leads instead to reverse T3 (rT3).
Since rT3 is a biologically inactive compound
[3], this route of metabolism has been termed
the “inactivating” pathway. A precise metabolic
role for rT3 has not been described, but diversion of T4 metabolism from the activating to the
inactivating pathway serves a nitrogen-sparing
and protective effect for the body during times
of stress and has been viewed as homeostatic.
After binding to a cellular receptor, the thyroid
hormones have both genomic and nongenomic
effects, the former leading to modulation in
expression of nuclear actions, whereas the latter
appears to involve plasma membrane/mitochondrial responses [4] (Table 6.1).
hyroid Hormone Effects
T
Hyper- and hypothyroidism, associated with either
excess or deficiency of TH, respectively, may
have a negative impact on exercise performance.
Although TH has pervasive effects on virtually
Triiodothyronine (T3)
HO
Thyroxine (T4)
O
CH2— CH— COOH
5' deiodinase
HO
O
NH2
CH2— CH — COOH
NH2
5 deiodinase
HO
O
CH2— CH— COOH
NH2
Reverse triiodothyronine (rT3)
Fig. 6.1 Thyroxine, triiodothyronine, and reverse triiodothyronine
6
Exercise and Thyroid Function
Table 6.1 Genomic and nongenomic actions of thyroid
hormones
Genomic actions of thyroid hormones
-Positive regulation
Sarcoplasmic reticulum calcium adenosine
triphosphatase
Myosin heavy chain α
β1-adrenergic receptors
Sodium/potassium adenosine triphosphatase
Voltage-gated potassium channels (Kv1.5, Kv4.2, Kv4.3)
Adenine nucleotide translocator 1
-Negative regulation
T3 nuclear receptor α1
Myosin heavy chain β
Phospholamban
Sodium/calcium exchanger
Adenylyl cyclase types V,VI
Nongenomic actions of thyroid hormones
Conductivity of sodium, potassium, and calcium
channels
Actin polymerization status
Activation of PI3K/Akt/mTOR signaling pathway
Deiodination and decarboxylation of T4 resulting in
thyronamine synthesis
all functions of the body, the following discussion
emphasizes thyroid-related influences on exercise
tolerance as mediated via involvement with cellular metabolism and the function of skeletal muscle
and the cardiac, vascular, and pulmonary systems.
ardiovascular Effects of Thyroid
C
Hormones
Cardiac performance is dependent on the contractility of the heart as well as systemic vascular
resistance. Resting tachycardia is very common in
hyperthyroidism, and many patients complain of
having a “racing” or “pounding” heart. The heart,
being itself a muscle, is affected by thyroid hormone levels as is skeletal muscle. The heart relies
mainly on serum T3 because there is no significant myocyte intracellular deiodinase activity [5].
TH can affect cardiac action via direct
genomic and nongenomic effects on cardiac
myocytes and hemodynamic alterations in the
periphery that result in increased cardiac filling and modification of cardiac contraction
[6]. TH mediates the expression of both struc-
87
tural and regulatory genes in the cardiac myocyte [5]. Thyroid hormone-responsive cardiac
genes include sarcoplasmic reticulum calcium/
adenosinetriphosphatase ([Ca2+]/ATPase) and its
inhibitor phospholamban, which are involved in
regulation of calcium uptake by the sarcoplasmic
reticulum during diastole [7], α- and β-myosin
heavy chains, the ion channels coordinating the
electrochemical responses of the myocardium:
sodium/potassium ATPase (Na+/K+-ATPase),
voltage-gated potassium channels (Kv1.5, Kv4.2,
Kv4.3), and sodium/calcium exchanger [6]. TH
increases the expression of β1-adrenergic receptors and downregulates TRα1 receptors [8, 9].
In summary, the genomic action of TH on the
heart involves genes which are largely responsible
for enhanced contractile function and diastolic
relaxation. Thus, T3 markedly shortens diastolic
relaxation, i.e., the hyperthyroid heart relaxes
with a higher speed (lusitropic activity), whereas
diastole is prolonged in hypothyroid states.
The nongenomic effects of TH on the cardiac myocyte and on the systemic vasculature
tend to occur rapidly. Schmidt et al. documented
that T3-enhanced myocardial contractility and
reduced systemic vascular resistance occur
within 3 min [10]. These rapid T3-mediated
effects include changes in membrane ion channels for sodium, potassium, and calcium; effects
on actin polymerization; adenine nucleotide
translocator 1 in the mitochondrial membrane;
and a variety of intracellular signaling pathways
in the heart and vascular smooth muscle cells [11,
12]. The actions on channels may determine set
points of myocardial excitability and duration of
the action potential and contribute to development of tachyarrhythmias [13].
Additional mechanism of T3 actions observed
in vitro includes rapid activation of phosphoinositide 3-kinases (PI3K) leading to protein kinase B
(Akt) phosphorylation that in turn translocates
to the nucleus and promotes mammalian target
of rapamycin (mTOR) phosphorylation [14]. As
mTOR is important to regulate ribosomal biogenesis and protein translation, the signaling pathway
described in these studies may underlie at least
one of the nongenomic mechanisms by which T3
regulates cardiac growth and hypertrophy.
D. Ylli et al.
88
Moreover, it has been discovered that deiodination and decarboxylation of T4 could generate
a biologically active metabolite, thyronamine,
which is characterized by actions opposite to
those of TH [15, 16]. It has been demonstrated
that thyronamine reduces cardiac output, heart
rate, systolic pressure, and coronary flow in isolated heart within minutes [16]. Conceivably, a
balance between T3 and thyronamine might be
responsible for maintaining cardiac homeostasis. Changes in this equilibrium might contribute to the cardiovascular alterations that occur in
patients with thyroid disease [17].
I n Vivo Animal Studies on the Role
of Abnormal Thyroid Function
in the Regulation of Cardiac
Response to Exercise
It has been believed that one of the main mechanisms of increased cardiac work during hyperthyroidism was the sensitization to catecholamines.
However, Hoit et al. in a study on thyrotoxic
baboons refuted a role of βl- or β2-adrenergic
receptors in any cardiac response to hyperthyroidism [18]. Interestingly, abnormal cardiac
response to exercise has been described as being
due to an inefficient use of chemical energy stored
in adenosine triphosphate (ATP). In hyperthyroid
hearts, a larger fraction of energy goes to heat
production, whereas in euthyroid animals more
is spent for useful contractile energy. Finally, TH
modifies the secretory activity of the heart—i.e.,
T3 has been found to increase mRNA and protein
levels of atrial natriuretic factor [19].
Several studies have indicated overactivation
of the renin–angiotensin–aldosterone (RAA)
system in hyperthyroid animals, documenting
increased plasma renin [20, 21] and upregulated
synthesis and secretion of angiotensinogen [22]
in hyperthyroid rats. In contrast, the plasma renin
activity is reduced in experimental hypothyroidism [20]. There is also an evidence of tissue-­
specific regulation of RAA. TH activates some
components of cardiac RAA, and hyperthyroidism can promote an increase in cardiac levels
of renin, stimulate Ang II generation [23], and
raise levels of AT1 and AT2 receptors [20]. In the
heart, Ang II exhibits growth-promoting effects
by inducing hypertrophy and fibrosis, mediated
by the AT1 receptor [24]. Although most of the
effects of Ang II related to cardiac remodeling
have been attributed to the AT1 receptor, the AT2
receptor is also involved in the development of
some cardiac hypertrophy models [25]. There are
several literature reports showing that AT1 receptor blockade and ACE inhibition attenuate or
prevent the development of cardiac hypertrophy
induced by TH in vivo [21, 26, 27]. Some authors
suggest that the mechanism of action of these
compounds is associated with the alterations in
calcium handling [28], while others suggest that
these drugs may inhibit AT1 receptor-induced
activation of PI3K/Akt/mTOR pathway [29, 30].
In hyperthyroidism structural remodeling such
as hypertrophy, left ventricular fibrosis, myocyte
lengthening, chamber dilatation, and decreased
relative wall thickness have been observed and
have been considered as likely to contribute to
global left ventricular functional impairment [31].
Clinical Findings
In thyroid disease, cardiac structures and function
may remain normal at rest; however, impaired
left ventricular (LV) function and cardiovascular adaptation to effort become unmasked during
exercise [32].
Hypothyroidism
Hypothyroidism has been associated with a
decrease in intravascular volume, stroke volume,
and cardiac index and an increase in systemic
vascular resistance, resulting in diastolic hypertension (Table 6.2) [33]. In patients with transient
hypothyroidism owing to thyroidectomy, radionuclide ventriculography and right heart catheterization revealed lower cardiac output, stroke
volume, and end-diastolic volume at rest, but
increased systemic peripheral resistance [34]. In
the same individuals, during exercise, heart rate,
cardiac output, end diastolic volume, and stroke
volume were higher when the patients were
euthyroid than when they were hypothyroid.
6
Exercise and Thyroid Function
89
Table 6.2 Cardiovascular changes observed in hyperand hypothyroidism
Heart rate
Vascular volume
Stroke volume
Cardiac output
SVR
LVEF
Rest
Exercise
Diastolic blood
pressure
Systolic blood
pressure
LV pre-ejection
period
LV ejection time
Hyperthyroidism
↑ NC
↑
↑
↑
↓
Hypothyroidism
↓NC
↓
↓
↓
↑NC
↑↓NC
↓
↓
↓NC
↓
↑NC
↑NC
↓NC
↓
↑
↓
↑
↑ increased, ↓ decreased, NC no change, SVR systemic
vascular resistance, LVEF left ventricular ejection fraction, LV left ventricular
The baseline LV ejection fraction (LVEF) and
peak LVEF were shown to be lower in hypothyroid subjects compared with their euthyroid
state, although with exercise, the rise of LVEF
in the two states was similar [35]. As assessed
by radionuclide-­gated pool ventriculography in a
younger group (average age 24 years), there was
no noticeable change in LVEF with hypothyroidism, although exercise tolerance did improve
after levothyroxine (LT4) replacement [36]. Even
hypothyroidism of brief duration of only 10 days
was associated with an impaired LVEF response
to exercise; LVEF response returned to normal with restoration of the euthyroid state [37].
Of interest, the patients still achieved the same
workload in either state.
Interesting observations have been found
in patients with subclinical hypothyroidism
(Sc-HypoT) defined as mild elevations of TSH
with normal levels of T4, fT4, T3, and fT3. It has
been a matter of investigative interest whether
the mild hypofunction associated with subclinical hypothyroidism affected any measureable
cardiac parameters.
An accurate assessment of left ventricular
function performed by Doppler echocardiography in patients with stable Sc-HypoT showed no
changes in left ventricle morphology. However,
the prolonged isovolumic relaxation time and a
reduced early-to-late ratio of the transmitral peak
flow velocities are suggestive of impaired diastolic function in the sense of slowed relaxation
[38].
In the same study, ten randomly selected
patients were re-evaluated after achieving euthyroidism by means of 6 months of LT4 administration. The treatment caused no change in the
parameters of left ventricle morphology, whereas
it normalized systolic and diastolic function.
Interestingly, although systemic vascular resistance was comparable in untreated patients and
control subjects, it was significantly decreased
after LT4 therapy. Similar findings have been
documented by Kahaly et al. [39], who assessed
cardiac function on effort and physical exercise
capacity showing no abnormalities in various
cardiac parameters at rest, either before or after
LT4 treatment. However, stroke volume, cardiac index, and peak aortic flow velocity were
significantly lower, and the pre-ejection period
was significantly prolonged during exercise in
the untreated patients versus controls. Other
authors confirmed early myocardial dysfunction
unveiling a difference in longitudinal systolic and
diastolic function reserve indexes during exercise in Sc-HypoT patients compared to controls
[40]. However, in a large-scale study, structural
changes were not observed when comparing
patients with normal TSH with patients with
TSH > 5 mIU/L [41]. Tadik et al. performing
3-dimensional echocardiography in 94 subjects
observed significantly reduced LV cardiac output
and ejection fraction in patients with Sc-HypoT
compared to both controls and the same patients
1 year after treatment [42]. Furthermore, when
women with Sc-HypoT perform physical activity, a slower HR kinetics (intended as time to
reach 63% of the HR at steady state) has been
observed in the transition from rest to exercise
compared with euthyroid women [43].
Evidence supporting reversible left ventricle
diastolic dysfunction in patients with subclinical hypothyroidism was documented employing
radionuclide ventriculography [44]. The authors
found that the time to peak-filling rate was prolonged in ten patients with Sc-HypoT compared
90
to ten normal control subjects. This accurate
index of diastolic function normalized after
achieving euthyroidism with LT4 therapy.
Abnormal diastolic function may impair coronary flow reserve. Hypothyroid individuals may
have a form of reversible coronary dysfunction as
found in a study of six patients undergoing stress
testing before and after LT4 replacement therapy. Prior to replacement therapy, SPECT scanning revealed notable regional perfusion defects
in four of six patients, which resolved within
8 weeks of LT4 therapy [45]. Similarly, Oflaz
et al. [46] found that coronary flow reserve was
lower in patients with Sc-HypoT than in euthyroid subjects. On the contrary, Owen et al. [47]
using stress echocardiography with i.v. dobutamine found no differences in resting global,
regional left ventricular function or regional
myocardial velocities during maximal dobutamine stress between patients and controls or in
patients treated with replacement therapy compared with baseline values.
To summarize, the vast majority of clinical
studies show impaired LV systolic and diastolic
function during exercise in patients with both
overt and subclinical hypothyroidism.
Hyperthyroidism
The effects of hyperthyroidism on cardiac function both during rest and exercise are numerous
(see Table 6.2) [33]. In thyrotoxicosis, the extent
of the various cardiac responses to excess TH is
somewhat dependent on the duration and severity of the disorder. Resting tachycardia, a slow
decline in postexercise heart rate (HR), atrial
fibrillation, decreased exercise tolerance, and,
rarely, congestive heart failure (CHF) are seen in
thyrotoxic patients. Cardiac complications from
hyperthyroidism tend to occur in patients with a
history of prior cardiac disease. Atrial fibrillation,
atrial enlargement, and CHF are more common
in patients over 60 years old with toxic multinodular goiter. Instead, cardiac valve involvement,
pulmonary arterial hypertension, and specific
cardiomyopathy are more common in Graves’
disease [48]. Augmented blood volume and
blood flow to the skin, muscles, and kidneys are
seen and may be owing to vasodilators released
D. Ylli et al.
secondary to increased cellular respiration [49].
A rise in cellular oxygen consumption leads to
a higher demand for oxygen and the need to get
fuel to the peripheral tissues [49]. An increase
in the velocity of cardiac muscle contraction is
present, as well as a rise in myosin ATPase activity [50]. Evaluation of systolic time intervals in
thyrotoxic subjects reveals a shortening of the LV
pre-ejection period along with quicker LV ejection time and isovolumetric contraction [33, 51].
Kahaly et al. analyzed alterations of cardiovascular function and work capacity using stress
echocardiography as well as spiroergometry in
subjects with untreated thyroid dysfunction, then
again after restoration of euthyroidism. At rest,
LVEF, stroke volume, and cardiac indices were
significantly increased in hyperthyroidism, but
exhibited a blunted response to exercise, which
normalized after restoration of euthyroidism.
During exercise, negative correlations were found
between free T3 (fT3) and diastolic blood pressure, maximal workload, HR, and LVEF. This
impaired cardiac response to exercise was specifically apparent in older subjects [52–54].
Of note, combined oral LT4/LT3 overdosage
has been reported to cause ST wave depressions
with treadmill stress testing that resolve with
the euthyroid state [55]. In general, diagnostic
treadmill testing is best delayed until patients are
euthyroid.
“Subclinical” hyperthyroidism (Sc-HyperT)
is a term that has been applied to patients with
undetectable levels of serum TSH, but with normal levels of T4, fT4, T3, and fT3. In one study,
there was no difference in LVEF at rest and exercise between Sc-HyperT and controls, whereas
overt hyperthyroid subjects had a reduction in
LVEF with exercise, increased HR, and cardiac
output at both rest and exercise [56]. Supporting
evidence was provided by a study performed in
1112 subjects with a 5-year follow-up in which
left ventricular mass divided by height did
not differ between subjects with and without
Sc-HyperT [57].
However, studies by Kaminski et al. indicated worse physical capacity in subjects with
Sc-HyperT and the possibility of improvement
after therapy. Compared with results after treat-
6
Exercise and Thyroid Function
ment, the end-diastolic and end-systolic volume indexes, stroke volume index, and cardiac
index were significantly larger in patients with
Sc-HyperT. Stroke volume index was negatively correlated with TSH and positively with
fT4 and fT3 values, and cardiac index was
positively correlated with fT4 and fT3 levels in
Sc-HyperT [58].
Analysis of the Framingham Heart Study
revealed that TSH was related to left ventricular
contractility in women with TSH < 0.5 mU/L
TSH [41]. Furthermore, thicker left ventricular
posterior wall, higher HR, and a lower achieved
maximum workload have been reported in
women with nontoxic multinodular goiter treated
with mildly suppressive levothyroxine therapy
compared to women not under treatment [59].
To summarize, LVEF, stroke volume and cardiac index, may be greater at rest in hyperthyroidism, but the lack of an increase in LVEF with
exercise seems to be a reproducible finding.
ffects on Systemic Vascular
E
Resistance (SVR)
TH causes decreased resistance in peripheral
arterioles through a direct effect on vascular
smooth muscle and decreased mean arterial
pressure, which, when sensed in the kidneys,
activates the RAA system and increases renal
sodium absorption. T3 also increases erythropoietin synthesis, which leads to an increase in red
cell mass. The combination of both leads to an
increased blood volume and preload. In hyperthyroidism, these effects increase cardiac output
by 50–300%, while a 30–50% reduction is seen
in hypothyroidism [5].
In the vascular smooth muscle cell,
TH-mediated effects are the result of both
genomic and nongenomic actions. Nongenomic
actions target membrane ion channels and endothelial nitric oxide (NO) synthase, which serves
to decrease SVR [60, 61]. Indeed, it was recently
reported that the PI3K/Akt signaling pathway
plays a role in T3-induced NO production by
vascular smooth muscle cells and by endothelial
cells [11, 62].
91
Furthermore, T3 has been shown to inhibit vascular remodeling via the inhibition of the cAMP
response element binding protein, a nuclear transcription factor involved in the remodeling process [63]. It seems also that voluntary exercise
training can improve long-lasting endothelial
dysfunction resulting from transient thyroid hormone deficiency in early life [64].
Clinical Findings
Hypothyroidism
Vascular control mechanisms may be abnormal
in hypothyroidism with blunted vasodilatation
secondary to reduced endothelium-dependent
vasodilatation [65, 66]. In overt hypothyroidism, arterial compliance is reduced, which
leads to increased arterial stiffness with higher
central augmentation pressure and lower pulse
wave velocities. These abnormalities were
reversible with adequate LT4 treatment [67,
68]. However, in subclinical hypothyroidism,
the study results have been equivocal. Several
studies have not found any association between
Sc-HypoT and blood pressure at rest [69–71].
In one cross-­sectional study [69], Sc-HypoT
was not associated with increased resting blood
pressure. Similar results were observed in the
cross-­
sectional Busselton thyroid study [70]
that included 105 subjects with Sc-HypoT and
1859 euthyroid controls from Western Australia.
On the other hand, two large population-based
studies with 5872 [72] and 30,728 [73] subjects
reported a modest association between high-­
normal serum TSH levels and resting blood
pressure. This observation has been confirmed
in other studies, suggesting that mild thyroid
­hormone deficiency also may affect vascular
tone [74–77]. Several studies documented an
improvement of SVR after LT4 replacement
[38, 78]. Endothelial dysfunction in patients
with hypothyroidism, borderline hypothyroidism, and those with high-normal TSH values
using flow-­
mediated arterial dilation (FMD)
has been demonstrated with TSH levels correlating inversely to endothelium-dependent dilatation [77]. Impaired endothelium-dependent
92
vasodilatation as a result of a reduction in nitric
oxide availability has been demonstrated in
Sc-HypoT by Taddei et al. [79].
Studies have also shown that FMD is associated with plasma osteoprotegerin levels in
hypothyroid patients [80]. Osteoprotegerin is
a member of the tumor necrosis factor (TNF)
receptor family involved in vasculature regulation and related with increased cardiovascular
mortality. In vitro studies suggest that TH and
TSH are involved in regulation of osteoprotegerin expression [81].
Hyperthyroidism
Endothelium-dependent arterial dilatation is
increased in hyperthyroid patients and is reversible after subtotal thyroidectomy [82]. Ojamaa
et al. [83] demonstrated vascular relaxation
due to the action of excess TH on the vascular
smooth muscle cells. Conceivably, an inability to
lower SVR during exercise in the hyperthyroid
state might lead to impaired exercise tolerance
[84]. In this regard, phenylephrine administration was associated with an increase in SVR and
a decrease in cardiac output not seen in euthyroid subjects [85]. On the contrary, a case-control
study of 42 patients with untreated overt hyperthyroidism documented similar systolic and diastolic blood pressures during maximal exercise as
in 22 healthy controls. Moreover, no changes in
systolic and diastolic blood pressure responses to
exercise were observed in these patients after restoration of euthyroidism during 6-month follow­up [52]. Similar findings hold true for the patients
with Sc-HyperT. In a recent population-based
prospective cohort study, Völzke et al. [86] found
that Sc-HyperT is not associated with changes in
blood pressure, pulse pressure, or incident hypertension. Some smaller studies have reported similar results [52, 87].
Effects in Muscles
TH plays a critical role in maintaining homeostasis and influencing the rate of metabolism and
energy expenditure. Skeletal muscles contribute
to about 20–30% of resting metabolic rate [88].
D. Ylli et al.
TH control the expression of myocyte-specific
genes coding for myosin isoforms [32], the Na+–
K+ ATPase pumps, and the Ca–ATPase canals
of the sarcoplasmic reticulum. This explains the
increase of contractility and relaxation of skeletal muscles observed in hyperthyroidism, as
opposed to hypothyroidism. In both cases muscle
performance is reduced, with accumulation of
lactic acid at exercise. This is because of defective pyruvate oxidation and proton expulsion in
hypothyroidism and of acceleration of glycolysis
in hyperthyroidism. Muscle glycolysis exceeds
mitochondrial oxidation enhancing the shunting of pyruvate to lactate, thus leading to an
increased lactic acid concentrations resulting in
intracellular acidosis. Furthermore, TH increases
fast myosin and fast-twitch fibers in skeletal muscle, which are less economic in oxygen utilization during contraction than slow-twitch muscle
fibers explaining impaired exercise tolerance.
I n Vivo Animal Studies on the Role
of Abnormal Thyroid Function
in the Regulation of Muscle Response
to Exercise
Animal studies of hypothyroidism reveal that
glycogen levels in muscle appear to be normal to
increased at rest, whereas during exercise, muscle utilization of glycogen rises as may lactate
production [89, 90].
In hypothyroidism, studies reveal a reduction
in flow to the fast-twitch type II fibers of high-­
oxidative type muscles [91] compromising exercise capacity via reduced oxygen delivery and
endurance through decreased delivery of blood-­
borne substrates [92, 93]. Additionally, decreased
mobilization of free fatty acids (FFA) from adipose tissue leads to reduced lipid delivery to
skeletal muscle [94]. After exercise the rate of
glycogenolysis exceeded those in controls, showing diminished oxidative capacity resulting in
lowering the ATP content. Thus, inadequate fuel
utilization may be considered as a factor limiting
ability for heavy exercise in hypothyroidism [89]
probably triggering compensatory mechanisms
in gene expression resulting in a slower striated
6
Exercise and Thyroid Function
muscle phenotype [95, 96]. Moreover, in distinction to hypothyroid individuals, muscle blood
flow is enhanced in hyperthyroid subjects including fast-twitch sections of muscle [94].
In induced hyperthyroidism, compared
to euthyroid control rats, the energy cellular
potential was increased during exercise, and
it remained higher after the recovery period
[97] testifying for an impaired cellular energy.
THs also promote expression of peroxisome
proliferator-­activated receptor-γ coactivator-1α
(PGC-1a), which mediates mitochondrial biogenesis and oxidative capacity in skeletal muscle.
Acute exercise increases deiodinase-2 expression
in skeletal muscle accelerating conversion of T4
to T3 which induces PGC-1a and its downstream
effect on mitochondria [98].
Whether physical activity can be recommended in hyperthyroidism is questionable. The
effect of T3-induced thyrotoxicosis on exercise
tolerance has been studied, with increases noted
in resting oxygen uptake and increased lactic
acid levels, protein breakdown, and loss of lean
body mass [99]. However, Venditti et al. demonstrated in vivo that moderate training attenuated T3-induced increases in hydrogen peroxide
(H2O2) production and, therefore, oxidative damage increasing antioxidant protection and
decreasing the reactive oxygen species (ROS)
flow from the mitochondria to the cytoplasmic
compartment [100]. Another study of leucine
supplementation in hyperthyroid rats demonstrated a positive effect in physical performance
compared to the non-treated group [101].
Clinical Findings
Hypothyroidism
Hypothyroidism is characterized by a
decrease in Ca2+ uptake and ATP hydrolysis by
sarcoplasmic/endoplasmic reticulum calcium
ATPase (SERCA; see Table 6.3) [102]. At least
mild elevations in creatine kinase levels are seen
in about 90% of hypothyroid patients [103]. In
hypothyroid subjects, the alterations in lipid,
protein, and carbohydrate metabolism in muscle
may have pronounced effects on muscle function.
93
Table 6.3 Muscle changes observed in hyper- and
hypothyroidism
Muscle strength
Type II fibers
Lactate: exercise
response
Sarcoplasmic
reticulum Ca2+
uptake
PCr/
Pi ratio—exercise
PCr recovery rate
Hyperthyroidism
↓
↑
↑
Hypothyroidism
↓
↓
↑
↑
↓
↑
↓
↑
↓
↑ increased, ↓ decreased, PCr/Pi phosphocreatine/inorganic phosphate, PCr phosphocreatine
Exercise may exacerbate this situation and be
associated with rhabdomyolysis [104]. Several
cases of rhabdomyolysis have been reported
[105, 106], and a relation to a reversible defect in
muscle glycogenolysis has been suggested [107].
In Hoffmann’s syndrome, another muscle disorder related to hypothyroidism, abnormalities
include increased muscle mass, muscle stiffness
and weakness, creatine kinase of as much as >10
times normal levels, and repetitive positive waves
on electromyography (EMG) [108]. Resolution
of symptoms is expected with thyroid hormone
replacement. EMG patterns that can be seen with
hypothyroidism include fibrillations, increased
polyphasic waves, unusual high-frequency discharges, and reduced motor unit recruitment [108].
An abnormal increase in lactate during exercise but not at rest has been described in subclinical hypothyroidism [109]. It was hypothesized
that mitochondrial oxidative dysfunction was
present and that this dysfunction worsens with
length of disease; glycolysis may exceed pyruvate oxidation explaining the lactate buildup.
Phosphorous nuclear magnetic resonance
spectroscopy (MRS) has been extensively used
to investigate noninvasively the energy metabolism of human muscle. It allows tracking of
real-time changes in the relative concentrations
of the metabolites that are involved in highenergy phosphate metabolism [110]. A study by
Kaminsky et al. performing MRS in hypothyroid
women subdivided into either moderate hypothyroidism, subacute thyroid deficiency, or severe/
94
chronic hypothyroidism demonstrated dysfunction of muscle bioenergetics with even mild TH
deficiencies [111]. Khushu et al. documented
similar abnormalities in the bioenergetic profile in 32 hypothyroid patients [110]. Similarly,
Bose et al. showed shifting of equilibrium of ATP
breakdown to ADP and inorganic phosphate (Pi)
after exercises confirming impaired oxidative
phosphorylation in mitochondria [112].
Haluzik et al. compared metabolic changes
in 12 hypothyroid women with those in 6 hyperthyroid and 12 euthyroid women. Compared to
healthy subjects, hypothyroidism was associated
with significantly decreased noradrenaline and
glycerol concentrations, whereas the opposite is
applied to hyperthyroid patients. These findings
suggest altered adrenergic and lipolytic activities
in thyroid disorders [113].
Whether the changes occurring in hypothyroidism are observed in subclinical hypothyroidism has been investigated. Changes in
phosphometabolites (increased phosphodiester levels and Pi concentration) were similar in
patients with overt hypothyroidism compared
to Sc-HypoT. However, impaired muscle oxidative metabolism was not observed in Sc-HypoT
patients [114].
Sc-HypoT in 3799 otherwise healthy subjects
was associated with a lower resting HR and a
significantly lower recovery HR [115]. While
Reuters et al. observed no changes in muscle
functional capacity in Sc-HypoT, symptoms of
cramps, weakness, and myalgia were more frequent compared to controls [116], and a lower HR
after exercise was observed [115]. Furthermore,
Tanriverdi et al. observed Sc-HypoT subjects to
have a higher arterial stiffness and lower physical
activity duration with a significant difference in
neuromuscular symptoms, muscle strength, and
functional exercise capacity assessed by a 6-min
walk test [117].
Hyperthyroidism
Hyperthyroid subjects also have impairment in
cellular respiration and reduced exercise endurance [109]. Excess heat generation from the
elevated metabolic activity associated with thyrotoxicosis and secondary hyperthermia may
D. Ylli et al.
adversely impact heat dissipation during exercise
and exercise tolerance. However, despite a baseline temperature increase of 0.5 °C in thyrotoxic
subjects, exercise-induced temperature rise has
been observed not to differ from that in controls
[118]. Reduced duration of action potentials
and increased polyphasic potentials can be seen
with thyrotoxicosis [119]. Muscle weakness is a
common complaint in patients with TH excess,
and a variety of investigations have addressed
muscle changes secondary to hyperthyroidism.
Hyperthyroidism is associated with an increase
in fast and a decrease in slow-twitch muscle
fibers. Thyrotoxicosis appears to induce an oxidative muscular injury secondary to an increase
in mitochondrial metabolism and a decrease in
glutathione peroxidase, which may be protective against such injury [120]. Glycogen is lower
at baseline in thyrotoxicosis and is utilized at a
faster rate with an associated increase of serum
lactate [121]. According to studies of Ribeiro
et al., glycogen storage in hyperthyroidism can
be differently distributed in tissues with lower
levels in the heart, liver, and soleus and higher
levels in mixed fiber type of gastrocnemius during regular swimming [122].
Thyrotoxic periodic paralysis (TPP) is an
unusual complication of hyperthyroidism more
typically seen in thyrotoxic Asian subjects,
although not exclusively so. Patients with TPP
suffer from attacks of para- or quadriplegia
incited by exercise, high-carbohydrate meals, or
high-salt intake [123].
The muscular function of these patients may
appear grossly normal before and between episodes, although some patients have a prodrome
of muscle stiffness and aching. The pathophysiology revolves around an imbalance in the Na+/
K+ pump. EMG studies reveal that the muscle has
reduced excitability during TPP episodes, and
low-amplitude muscle action potentials are seen
following a paralytic episode [124]. Decreased
compound motor action potential amplitudes are
found postexercise in TPP [125] and improve
following treatment [126]. Of note, muscle fiber
conduction velocity measured in two patients
with TPP was within normal limits during
paralysis episodes, although muscle strength
6
Exercise and Thyroid Function
was reduced by 40% during an attack [127]. A
comparison of the electrophysiologic response to
prolonged exercise between thyrotoxic patients
with and without TPP demonstrated a preexisting latent abnormal excitability of the muscle
membrane in TPP [128]. TH regulates muscle
membrane excitability by increasing Na+/K+
pump-dependent potassium influx [129]. Adding
to our insight into the pathophysiology of TPP is
the recent discovery of KCNJ18 gene mutations
in a third of TPP patients which alter the function of an inwardly rectifying potassium channel
named Kir2.6 [130].
There are also a few case reports documenting
rhabdomyolysis as a complication of hyperthyroidism [131–133].
Some authors describe significant metabolic changes in exercising muscle exposed to
excess TH. Reduced metabolic efficiency of
skeletal muscle energetic with decreased phosphocreatine (PCr) in hyperthyroid patients has
been documented by MRS [134]. Under thyrotoxic conditions, ATP is promptly depleted, and
myopathy easily develops, as the intramuscular
glycogen content decreases due to the suppression of glycogenesis and glycogenolysis. During
vigorous exercise, glycogen is rapidly consumed,
and ATP consumption by the skeletal muscles
increases more than the ATP supply. At that time,
the compensatory mechanisms include involvement of purine catabolism as a source of energy
[135, 136]. Fukui et al. compared the levels of
glycolytic metabolites (lactate and pyruvate) as
well as purine metabolites (ammonia and hypoxanthine) in treated and untreated Graves’ disease patients vs. normal controls [137]. The study
revealed that glycolysis and purine catabolism
were remarkably accelerated in hyperthyroidism and thyrotoxic myopathy could be closely
related to the acceleration of purine catabolism,
which can be normalized only after long-lasting
euthyroidism. Moreover, such acceleration of the
purine nucleotide cycle is thought to be in part a
protective mechanism against a rapid collapse of
the ATP energy balance in exercising muscles of
patients with hyperthyroidism [137, 138].
Another important question facing clinicians
is the effect of treatment with suppressive doses
95
of LT4 necessary in some patients with differentiated thyroid cancer. Vigario et al. [139] addressed
this question and documented that muscle mass
was lower in the patients on suppressive LT4
treatment than in euthyroid control subjects, but
aerobic training, twice a week, during 3 months
partially reversed this deteriorating effect of
excess TH on muscle mass. Greater attention
should be paid to elderly men with subclinical hyperthyroidism who may have accelerated
poor physical performance. Also in euthyroid
man, higher FT4 was predictive of a lower Short
Physical Performance Battery score at the 3-year
follow-up [140].
Effects on Pulmonary Function
Performance of any strenuous activity especially
of endurance training requires the ability of the
respiratory system to augment oxygen utilization. Exercise capacity, the maximal capacity for
oxygen consumption (VO2 max), and endurance,
the ability to perform prolonged exercise at 75%
VO2 max, are the two main components of exercise tolerance [141].
Clinical Findings
Large goiters, especially firm, nodular substernal goiters, can cause an extrathoracic tracheal
obstruction, which can limit air flow to the
lungs [142].
Hypothyroidism
Altered TH levels can lead to impairment in
optimal pulmonary function. Myxedema or profound hypothyroidism is associated with alveolar
hypoventilation related to a reversible reduction
in hypoxic ventilatory drive [143]. Reductions in
lung volumes are seen and include vital capacity, total lung capacity, functional residual capacity, and expiratory reserve volume, as well as a
decrease in diffusing capacity for carbon monoxide (DLCO) [144]. LT4 replacement therapy
is associated with resolution of the aforementioned changes, but a concomitant reduction in
96
patient weight may also be an important factor
in pulmonary function improvement [145]. Frank
respiratory failure is unusual. During exercise,
hypothyroid subjects were characterized by
reduced forced vital capacity and tidal volume
at the anaerobic threshold [146]. Also, the increment of minute ventilation and oxygen uptake
was significantly lower.
A study in women with subclinical hypothyroidism demonstrated a slower VO2 kinetics (defined as the time needed to reach 63% of
change in VO2) in both the onset and recovery of
exercise and a higher oxygen deficit compared to
euthyroid subjects [147]. Conceivably therefore,
it seems that levothyroxine treatment of mild or
subclinical hypothyroidism can decrease oxygen
uptake, improve minute ventilation and cardiopulmonary exercise performance, and improve
the ability in these patients to carry out activities
of daily life [148].
Hyperthyroidism
Thyrotoxicosis has been implicated as a primary
cause of decreased cardiorespiratory exercise
tolerance [52, 149, 150]. In hyperthyroidism,
already at rest, cardiorespiratory capacity is
maximally increased, leading to a limited functional reserve, which may explain the inadequate
response of ventilation [53]. Dyspnea on exertion
is a common complaint although the causes of
this symptom remain unclear and may vary from
one patient to another [151]. In hyperthyroidism,
the respiratory systems adjust to the increased
oxygen demand by increasing respiratory rate
and minute ventilation [149]. Alveolar ventilation remains normal, but a rise in dead space
ventilation is seen, and also the amount of oxygen diffusion from alveoli to the blood may be
reduced during periods of strenuous exercise in
thyrotoxicosis [152].
Pulmonary function is dependent on not just
intrinsic lung function but also the accessory
muscles for respiration. Pulmonary compliance
and airway resistance tend to remain unchanged,
whereas vital capacity and expiratory reserve
volume are reduced, implicating respiratory
muscle weakness [153]. Other supporting evidence for respiratory muscle dysfunction in
D. Ylli et al.
thyrotoxic patients is the reduction of maximal
inspiratory and expiratory efforts, which are
seen to resolve on restoration of euthyroidism
[154]. It appears that ventilation increase beyond
the oxygen uptake is related to the dead space
ventilation [155]. These changes also appear to
resolve with appropriate therapeutic intervention
[155]. Furthermore, changes in TH levels modify
diaphragmatic function as well as muscle fiber
type. Goswami et al. documented a more marked
functional weakness of the diaphragm in Graves’
disease during maximal respiratory maneuvers,
indicating a diminished diaphragmatic reserve
that could cause dyspnea on exertion. These
changes were reversible after achieving euthyroidism [156].
With cardiac and muscular function being
adversely affected by excess TH, one would
postulate that work capacity must be reduced in
hyperthyroid individuals. A study of maximum
power output in hyperthyroid individuals with
measurements of work capacity both while thyrotoxic and then euthyroid revealed a 19% increase
from a low maximum power output during the
thyrotoxic phase compared to the euthyroid state
3 months later. A subset of patients were retested
12 months later, and maximum power output
in comparison to controls was in the low normal range and represented a +13% rise from the
3-month test [157]. Oxygen uptake at maximal
effort was low during thyrotoxicosis and did not
increase at 3 and 12 months. Net mechanical efficiency was also low at baseline and returned back
up to normal only by 12 months. Kahaly et al.
showed reduced forced vital capacity, 1-second
capacity, and increased respiratory resting oxygen uptake (VO2) rate in hyperthyroid patients
compared to euthyroid controls. During exercise,
decreased tidal volume at the anaerobic threshold
was observed as well as a lowered increment of
minute ventilation, VO2, and oxygen pulse [53].
The studies are equivocal in terms of the effect
of treatment with suppressive doses of LT4 on
exercise capacity. Some studies revealed similar
blood pressure, heart rate, VO2, VCO2, and anaerobic threshold response to exercise in LT4-treated
patients as in healthy control subjects [158].
Other studies found that ventilation parameters
6
Exercise and Thyroid Function
between patients and controls were comparable
only at rest, but the patients treated with suppressive doses of LT4 had a worse response to exercise (i.e., lower maximal workload, lower peak
VO2, and lower anaerobic threshold) [159].
In conclusion, analysis of respiratory gas
exchange showed low efficiency of cardiopulmonary function, respiratory muscle weakness,
and impaired work capacity in hyperthyroidism which was reversible with restoration of
euthyroidism.
xercise and Thyroid Axis Response
E
Exercise is a stressful situation that challenges
body homeostasis, so that the organism has to
reestablish a new dynamic equilibrium in order
to minimize cell damage.
One of the systems affected is the hypothalamic–pituitary–thyroid (HPT) axis [160].
Data demonstrate that voluntary exercise
adapts the status of the HPT axis, through pathways that are distinct from those observed during
food restriction or repeated stress [161]. Lesmana
et al. suggested that alteration in TH signaling
(increased TRβ1 expression) and TSH reduction observed in vitro after moderate training can
contribute to the metabolic adaptation of skeletal
muscle to physical activity [162].
Although the belief that a different normal
range for thyroid hormones may apply in athletes compared to healthy nonathletes may be
considered, data on the effects of exercise on
TH metabolism have been inconsistent or even
contradictory (see Table 6.4). These divergent
results may be due to differences in the intensity
of work, duration of exercise, and frequency and
design of the training program and to differences
in gender, age, and baseline individual physical
status of the subjects. In addition, different duration of studies, timing of sampling after exercise,
and methodological factors in hormonal assay
and data analysis may also be responsible for the
discrepancies.
Some studies indicated no major changes in the
thyroid axis response to exercise. For example, a
study of 26 healthy males, given identical diet
and physical activity for a week before the test,
revealed an increase in T3, T4, and TSH imme-
97
diately after exercise. However, it seems that the
changes were mainly due to hemoconcentration,
since they became insignificant after adjustment
for hematocrit (Hct) [163]. Another study in subjects undergoing different exercise endurance
showed similar results: no significant change in
FT4 and a small increase (partially from hemoconcentration) in serum T3 and rT3 [164].
Interestingly, some studies indicate that TSH
increases after exercise with the response dissipating with repetitive testing, which was suggested to indicate a psychological influence
on the TSH rise [165]. In another study a fT4
increase of 25% was seen postexercise [166], but
the increase may have been confounded by assay
interference by an associated rise in FFAs. TSH
also rose by 41%, but could not be correlated
with T4/T3 levels.
A rise in TSH was seen with both short-­
duration graded exercise and prolonged exercise,
but the latter had a peak of 33% lower than with
graded exercise [167]. Another study compared
the effect of submaximal and maximal exercise
effect on TH levels [168]. Maximal exercise
was associated with a decrease in TSH, FT4,
and ­stable rT3 and rises in T3 during activity,
whereas submaximal exercise was associated
with an increase in TSH, but T3, rT3, and FT4
were unchanged. [168]. Also, when comparing
intensive exercise intervals with steady-state
endurance exercise, Hackney et al. observed that
the change in TH levels was present 12 hours
post exercise only in the intensive exercise group
implying a longer period necessary for TH to
return to normal. In both groups an increase in
fT3, fT4, and rT3 was present immediately post
exercise with a decrease in fT3 and increase of
rT3 12 hours post exercise only in the intensive
exercise group [169].TH changes in ultradistance
and long-distance runners have also been investigated. Hesse et al. studied the effect of three distances of 75 km, 45 km, and marathon (42.2 km)
with the subjects performing the 45-km run
being slightly older than the other two groups. T4
increased in the 75 km and marathon group and
decreased together with T3 in the 45-km group
postrace. rT3, measured only in the marathon and
75-km groups, rose in both groups. The authors
D. Ylli et al.
98
Table 6.4 Reported changes in hypothalamus–pituitary–thyroid axis in association with exercise
Caloric
status
NA
NA
NA
NA
NA
NA
TSH T4 fT4 T3 fT3 rT3
↑
↑
↑
↑
NC
↑
↓
NC
↓
↑
↑
↓
↑
NC
Maximal treadmill
exercise
Sufficient
NC
Aerobic exercise
Running
Running
Running
Runners
Ultradistance
Ultradistance
Ultradistance
Intensive exercise
Intensive exercise
Steady state
exercise
Steady state
exercise
Swimming
Swimming
Swimming
Swimming
Ballet
High-intensity
resistance training
High-intensity
endurance training
Deficient
NA
NA
NA
Deficient
NA
NA
NA
NA
NA
NA
Chronic endurance
exercise
Chronic endurance
exercise
High-altitude
exercise
NA
Reference
[165]
[166]
[173]
[173]
[188]
[181]
Exercise type
Pre-exercise
Ergometry
Ergometry
Ergometry
Ergometry
Chronic ergometry
[163]
[2]
[168]
[174]
[168]
[183]
[170]
[170]
[170]
[169]
[169]
[169]
[169]
[164]
[176]
[176]
[176]
[197]
[195]
[195]
[180]
[183]
[196]
↓
NC
↑
NC
↓
NC
NC
↑
NC
↓
↓
↑
NC
NC
NC NC
↑
↓
NC
↑
↓
↓
↑
↓
↑
↑
↓
↑
↑
↓
NA
NA
NA
NA
NA
NA
NA
↑
NC
↓
NC
↓
NA
↑
NC
NC
↑
NC
↓
NC
NC 12 hours post exercise
↑
NC
NC
NC
NC
↑
NC
↓
NC
NC
↓
NC ↓
↓
↓
↓
NA
NC
↓
NA
NC
NC
Comments
Anticipation of exercise
Normal TRH stim
Untrained athletes
Well-trained athletes
Glucose infusiona
Recreational athletes NC TSH
response to TRH
Transient changes in TH values
reflected transcapillary movements of
water
Not seen in energy-balanced group
↑
NC Maximal exercise
Endurance athletesb versus controls
NC Submaximal exercise
Prevented by caloric increase
75 kmc
↑
45 kmc
42.2 kmc
↑
Post exercise
↑
12 hours post exercise
↑
Post exercise
↑
↓
↓
20oCd
26 °C
32 °C
Leptin levels correlated with TSH
levels
Same group of rowers underwent
3 weeks of resistance and 3 weeks of
endurance training
Identical twins
↓
Amenorrheice
Increased GH/IGF-1 axis and low T3
syndrome
T4 thyroxine, T3 triiodothyronine, fT4 free thyroxine, fT3 free triiodothyronine, rT3 reverse triiodothyronine, TSH
thyrotropin, TRH TSH-releasing hormone, NA not applicable, NC no change, ↑ increase, ↓ decrease
a
A glucose infusion blunted the exercise-induced changes of rT3, T3, and T4
b
Endurance athletes had balanced increase in T3 production and disposal rates in comparison to active and sedentary
men
c
TSH, T4, and T3 are lower in older runners, whereas faster runners had higher T4 and TSH in relation to slower
runners
d
High TSH with longer cold water exposure
e
T4/fT4, T3/fT3, and rT3 were lower in exercising amenorrheic versus sedentary group. The eumenorrheic exercise
group only has a slightly lower fT4 level, but T4 and T3 were slightly lower than the eumenorrheic sedentary group
6
Exercise and Thyroid Function
speculated whether the increase in rT3 might be
protective against excess glucose metabolism,
especially if intracellular glucose deficiency were
present [170]. Semple et al. reported on marathon
runners revealed no change in TSH, T4, T3, or
rT3 levels before and after the marathon [171].
However, another study revealed an increase in
TSH and fT4 post-marathon, with a decrease in
fT3 and rise in T4 to rT3 conversion, which was
still detectable 22 hours following race completion [172].
The level of training of athletes has been shown
to affect the TH response to acute exercise. In one
investigation, untrained athletes had a rise in T3,
a decrease in rT3, and no change in T4, whereas
the well-trained athletes were found to have a rise
in rT3, no change in T3, and a decrease in T4 levels. It was hypothesized that the rT3 elevation in
well-trained athletes might be adaptive to a more
efficient cellular oxidation process [173]. Of note
in another study, Rone et al. found an increase in
T3 production and turnover in well-trained male
athletes in comparison to sedentary men [174].
Following a treadmill stress test, TH levels and
TRH simulation revealed responses similar in
nature among sedentary subjects, regular joggers,
and trained marathon runners [175].
Variation in ambient temperature appears to
alter the body’s TH response to exercise. One
study looking at TH differences in swimmers
exercising in different water temperatures demonstrated that TSH and fT4 rose in the colder
water, were unchanged at 26 °C, and fell at the
warmer temperature, but T3 levels were not
affected [176]. Cold receptors appear to regulate
a rise in TRH and TSH level in cold water, and
exposure duration may affect the peak TSH with
higher levels owing to longer times in the water
[177, 178].
The chronic effects on thyroid hormone
parameters have also been studied in endurance-­
trained athletes. The results of the studies conflict with regard to whether or not baseline TH
levels are shifted in well-trained athletes [179].
Identical twins studied during an observed
93 days endurance training period with stable
99
energy intake had an average 5-kg weight loss
(primarily fat) and lower baseline fT3, T3 by the
end of the exercise period [180]. A shorter study
in recreational athletes over 6 weeks revealed no
change in TSH or TSH response to TRH stimulation during exercise although the exercise endurance improved [181]. Also no difference was
reported in baseline values for T4, T3, and TSH
between endurance athletes and sedentary controls over time [174].
Radioactive iodine uptake (RAIU) may be
altered secondary to chronic exercise since a
lower thyroid uptake of 123I has been found in
regular exercising rats and humans in comparison
to sedentary subjects [179].
Energy balance plays a role in the body’s TH
response to exercise. Data on the response of
TH to fasting or malnutrition [182] suggest that
the T3 decrease and rT3 increase could reflect a
regulatory mechanism to regulate catabolism and
energy expenditure. Of note, T3 and rT3 return to
normal with refeeding. Loucks and Heath [183]
found a decrease in T3 (–15%) and fT3 (–18%)
along with an increase in rT3 (+24%) in healthy
women undergoing aerobic exercise testing with
low-caloric intake. However, this “low T3 syndrome” was not seen in individuals receiving a
normo-caloric diet in balance with their energy
expenditure. Other studies demonstrated that the
reduction of energy availability from 45 kcal/
kgFFM/day to 10 kcal/kgFFM/day was associated with a decrease in T3 levels in women
undergoing 5 days of exercise (see Fig. 6.2a)
[184, 185]. Especially in amenorrheic athletes,
T3 levels have been found to be lower than in
eumenorrheic athletes and sedentary women perhaps suggesting a generalized reduction of the
energy-­consuming process (see Fig. 6.2b) [185].
Furthermore, the observed correlation between
T3 levels and osteocalcin suggests a possible role
in collagen formation and matrix mineralization,
thus contributing to the athlete triad characterized as a low energy availability or eating disorder, dysmenorrhea, and low bone density [186].
Interestingly, low-caloric diets high in carbohydrate appear to blunt the drop in T3 compared
D. Ylli et al.
100
a
b
110
Triiodothyronine (%ES)
110
Triiodothyronine (%45)
Fig. 6.2 Triiodothyronine
(T3) levels (mean ±SE).
(a) Reduction of T3 levels
in exercising women after
5 days at energy
availabilities of 45, 30, 20,
and 10 kcal/kgFFM/day.
(b) Amenorrheic athletes
(AmA), eumenorrheic
athletes (EuA), and
sedentary women (EuS).
Low T3 levels in the
athletes suggest a
generalized reduction in
the rates of energy
consuming processes
100
90
80
70
10
20
30
45
Energy availability
(kcal/kgFFM/day)
to low-carbohydrate intake [187]. Moreover,
glucose infusion has been found to diminish the
increase in rT3 and T4 along with decrease in T3
[188].
In a military study, rangers were assessed over
4 days of grueling training in conjunction with
sleep and caloric deprivation. The training was
associated with an initial increase of TH during
the first 24 h. After 4 days of training, there was
a gradual decrease in T4, fT4, and T3 (65%),
whereas rT3 continued to rise. The group that
received a higher caloric intake, and therefore
less energy deficiency, had a continued increase
in T3 and T4. In the energy-deficient groups,
TSH decreased during the first day and remained
low throughout the training period. The response
of TSH to TRH was reduced in all groups, but
much less so in the energy-sufficient group [189].
The detected energy deficiency correlated with a
decrease in T3 and increase in rT3 in this study
[189]. Hackney et al. have demonstrated that
these responses to military exercises and their
relation to energy deficiency exist in extreme
cold as well as hypoxic environments [190, 191].
Higher-altitude exposure has been shown to be
associated with an increase in T4 and fT4 [192].
Furthermore, although Stock et al. reported that
exercise at elevated altitudes is also notable for a
significant increase in T4 and fT4 with even mild
activity [193], not all studies entirely agree with
these observations [191].
100
90
80
70
AmA
EuA
EuS
Subject group
Animal studies revealed an increase in serum
T3 immediately after exercise, with a gradual
decrease thereafter to significantly lower values
than in controls. Concomitantly, T4 levels progressively increased, resulting in the T3/T4 ratio
being significantly decreased 60 and 120 min
after the exercise, indicating impaired T4-to-T3
conversion [194].
Simsch et al. assessed hypothalamic–thyroid axis and leptin concentrations in six highly
trained rowers. After 3 weeks of resistance training, a reduction in TSH, fT3, and leptin was
found, while fT4 was unchanged. Interestingly,
leptin levels correlated with basal TSH levels. In
contrast, after 3 weeks of endurance training, a
significant increase of TSH was observed. The
authors interpreted these data to indicate that
depression of the hypothalamic–thyroid axis and
leptin is associated with training intensity [195].
Studies of Benso et al. also support the concept
of low T3 syndrome as an adaptive mechanism
to intense training as was seen in nine male
well-­trained climbers studied after climbing Mt.
Everest and resulting in a low T3 syndrome with
no significant change in ghrelin and leptin despite
decrease in body weight [196].
Relative to women, amenorrhea is commonly
seen in well-trained female athletes. One study
found that amenorrheic subjects had lower T4
and T3 levels than the eumenorrheic groups, but
the trained eumenorrheic females had slightly
6
Exercise and Thyroid Function
lower T4 and T3 levels than the eumenorrheic
nonathletes as well [197]. Of interest, the amenorrheic athletes tended to eat less fat and eat
more carbohydrates with a similar caloric intake
in comparison to the two other groups with more
normal menstrual function. Also, the amenorrheic exercise group trained more hours and more
strenuously than the other two groups. Oxygen
uptake (VO2) was similar in the trained groups,
who also weighed less and had lower body fat. As
measured by 31phosphorous magnetic resonance
spectroscopy (31P-MRS), inorganic phosphate/
phosphocreatine (Pi/PCr) was not different at rest
or at exercise, and pH did not differ at any activity
level. However, PCr recovery was substantially
faster in the eumenorrheic endurance-trained
group than in the eumenorrheic nonathletes and
amenorrheic athletes, and the Pi/PCr recovery
was only different between the eumenorrheic-­
trained athletes and nonathletes [197]. PCr
recovery is related to oxidative metabolism, and
the fast recovery in trained eumenorrheic athletes
indicates a potentially more efficient metabolism. The other parameters examined for exercise metabolism in these subjects were similar.
Contrastingly, in another study, levels of TSH,
T3, and T4 were not found to be different in oligomenorrheic heavily trained adolescents versus
adolescent athletes without “strenuous” exercise
with regular menses [198].
Summary
In summary, the thyroid function changes secondary to exercise represent complex physiologic
responses, which are difficult to characterize
fully. Mitigating factors in the TH response to
exercise include age, baseline fitness, nutrition
status, ambient temperature, altitude, as well as
time, intensity, and type of exercise performed.
Another important factor in interpretation of the
extant literature is that not all TH blood tests
were assessed in every study. Moreover, older
studies employed less sensitive assay techniques,
whereas various assays have improved over time.
The detection of increased FFA in several studies, which may interfere with some TH assays,
101
also cannot be overlooked. However, despite
these issues, a review of the literature does reveal
certain trends (Table 6.4). One of the more consistent findings is that rT3 tends to increase with
exercise especially with associated caloric energy
deficiency or ultradistance exercise activities.
However, TSH appears to be unaffected by exercise in about 50% of studies with an increase in
TSH secondary to cold exposure being a noted
exception. T4 was found to increase in 46%,
decrease in 26%, and be unchanged in 28% of
investigations, although an increase was more
typically found with caloric energy deficiency,
cold exposure, or ultradistance exercise; fT4 follows a similar pattern to T4. T3 was found to
be decreased or be unchanged in 73% of study
samples and usually is low with caloric energy
deficiency (as in low T3 syndrome); fT3 when
measured tended to follow the T3 pattern.
Many of the TH changes seen especially in
athletes with negative energy balance appeared
to be reversed with either a high-carbohydrate
intake or even glucose infusion. Although well-­
trained athletes may exhibit an increased production and turnover of T4, baseline TH levels do
not appear to be affected substantially by chronic
exercise (i.e., endurance).
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7
The Male Reproductive System,
Exercise, and Training: Endocrine
Adaptations
Fabio Lanfranco and Marco Alessandro Minetto
Introduction
Androgens exert strong anabolic effects on skeletal muscle protein synthesis [1, 2], satellite cell
number [3], and skeletal muscle growth [4, 5].
Because these changes are of great importance
to muscle mass and strength, androgens have
been recognized as important hormones that
influence sports performance [6]. Exerciseinduced changes in testosterone concentrations
can moderate or support neuromuscular performance through various short-term mechanisms
(e.g., second messengers, lipid/protein pathways, neuronal activity, behavior, cognition,
motor system function, muscle properties, and
energy metabolism) [7].
On the other hand, the gonadal axis function
is strongly affected by physical exercise
depending on the intensity and duration of the
activity, the fitness level, and the nutritionalmetabolic status of the individual [8–10].
Moreover, circulating testosterone and its bioavailable fractions are affected by weight and
F. Lanfranco (*)
AOU Citta della Salute e della Scienza di Torino,
Division of Endocrinology, Diabetology and
Metabolism, University of Turin, Department of
Medical Sciences, Turin, Italy
e-mail: fabio.lanfranco@unito.it
M. A. Minetto
Division of Physical Medicine and Rehabilitation,
Department of Surgical Sciences, University of Turin,
Turin, Italy
age. They are also changed by different kinds of
stress which may appear as physical stress (i.e.,
endurance training, sleep deprivation in extreme
sports, changes of air pressure in altitude training) or mental stress in relation to sport events
and training [9, 10].
The purpose of this chapter is to illustrate the
physiologic and pathologic changes that occur in
the male gonadal axis secondary to acute exercise
and chronic exercise training.
hysiology of the Male Gonadal
P
Axis
The male gonadal axis consists of the testes and
the hypothalamus-pituitary unit that controls
their function. The testes possess a dual function, i.e., the production of androgens and of the
sperm.
Figure 7.1 depicts an outline of the male
gonadal axis and of the hormonal regulation of
the testicular function.
The pituitary gland is the central structure
controlling gonadal function: it releases the
gonadotropins luteinizing hormone (LH) and
follicle-stimulating hormone (FSH) and is regulated by the hypothalamic gonadotropin-­
releasing hormone (GnRH), which is secreted in
a pulsatile fashion with peaks every 90–120 min.
GnRH secretion is modulated by a network of
excitatory and inhibitory inputs that include
either a central control exerted by distinct
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_7
109
F. Lanfranco and M. A. Minetto
110
Cortex
DA
Stress
Nutrition
Exercise
–
PRL
–
Hypothalamus
GnRH
–
+
–
–
+
–
–
+
GABA
–
NPY
Leptin
IL-1
–
+
NE
CRH Cortisol
Serotonin
β-endorphins
+
Ghrelin
–
LH
FSH
+
+
Ghrelin
CRH
Cortisol
–
+
Inhibins
Activins
–
–
Estradiol
Testosterone
Leydig cell
DHT
Sertoli cell
Sperm
–
ROS
Fig. 7.1 Schematic diagram of the male gonadal axis.
CRH corticotropin-releasing hormone, DA dopamine,
DHT dihydrotestosterone, FSH follicle-stimulating hormone, GABA gamma-aminobutyric acid, GnRH
gonadotropin-­releasing hormone, IL-1 interleukin-1, LH
luteinizing hormone, NE norepinephrine, NPY neuropeptide Y, PRL prolactin, ROS reactive oxygen species
subgroups of neurons afferent to the GnRHsecreting neurons or the peripheral gonadal
steroid feedback [11].
The hypothalamic kisspeptin system exerts a
fundamental control in the activation of GnRH-­
secreting neurons at puberty [11]. In addition,
several neurotransmitters and neuromodulators
are proposed to influence GnRH secretion: the
noradrenergic system and neuropeptide Y
(NPY) show stimulatory activity, whereas interleukin-1, opioid peptides, dopamine, serotonine,
and gamma-aminobutyric acid (GABA) are
inhibitory.
Another important peptide regulating the
GnRH secretion is leptin, a peptide hormone
secreted by the adipose tissue that helps to regulate the energy balance and mirrors the amount of
energy reserve. Leptin purportedly plays a key
role either by signaling to the central nervous
system the information regarding the amount of
available fat stores or by enabling the activation
of the gonadal axis through the GnRH secretion
7
The Male Reproductive System, Exercise, and Training: Endocrine Adaptations
when convenient [11]. Specifically, leptin has
been shown to stimulate GnRH and gonadotropin
secretions [12]. Additionally, ghrelin, a peptide
hormone with growth hormone-releasing action,
exerts multiple endocrine and non-endocrine
effects including inhibition of the gonadal axis at
both the central and peripheral level [13].
Another important mechanism that dynamically controls GnRH synthesis and release is represented by the gonadal steroid feedback. In man,
the major hormone controlling GnRH secretion
is testosterone, which inhibits gonadotropin
secretion via negative feedback both at the hypothalamic and pituitary level. Dihydrotestosterone
(DHT) and estradiol also modulate gonadotropin
secretion acting at the hypothalamic and/or pituitary level [11, 12, 14, 15]. Noteworthy, the kisspeptin system is implicated in the transmission of
both negative and positive feedback of sex steroids on GnRH neurons [11].
Finally, the adverse effect of stress on reproductive function is well known. Several hormonal
factors are involved: corticotropin-releasing hormone (CRH) inhibits GnRH secretion, prolactin
(PRL) further reduces the GnRH pulse rate [14],
and cortisol inhibits both the hypothalamus-­
pituitary and gonadal functions.
LH and FSH are produced and secreted by the
gonadotropic cells of the anterior pituitary. LH
regulates testicular androgenesis, whereas FSH,
together with locally produced testosterone, is
responsible for spermatogenesis. LH binds to
specific receptors on the surface of Leydig cells
in the testis and regulates the biosynthesis of testosterone. FSH binds to receptors on the Sertoli
cells and promotes spermatogenesis: in addition
to a number of other proteins, the hormones
inhibin B and activins are formed in the Sertoli
cells under the influence of FSH. Inhibin B plays
an important role in the feedback regulation of
FSH secretion, whereas the physiological role of
activins has not been conclusively clarified thus
far [14, 16].
Testosterone is the most important steroid
produced by the testis and is responsible for the
development and maintenance of male sex
characteristics as well as a number of other anabolic and metabolic effects (e.g., muscle and
111
bone metabolism). Testosterone is produced
primarily in the Leydig cells of the testis. It
may be further metabolized into a more potent
androgen, DHT. Normal testosterone concentrations in adult males range between 12 and
30 nmol/l: testosterone concentrations in blood
follow a circadian rhythm with higher levels in
the morning hours and about 25% lower levels
in the evening [12, 17].
ffects of Physical Exercise
E
on Testicular Steroidogenesis
hort, Intense Exercise Increases
S
Circulating Testosterone
The effects of physical activity on the male
gonadal axis vary with the intensity and duration of the activity, the fitness level of the individual, and his nutritional-metabolic status.
Relatively short, intense exercise usually
increases, while more prolonged exercise usually decreases serum testosterone levels [8, 9,
18, 19]. Increased blood testosterone levels have
been reported during relatively strenuous free
and treadmill running, weight training, rock
climbing, and ergometer cycling [20–22]. Shortterm sprints can be seen as strength outburst and
are comparable to resistance exercise rather
than endurance exercise: in fact, sprint exercise
increased blood testosterone concentrations in
adolescent boys [23].
The testosterone response increases with
increased exercise load [24]. Similar workloads
produce similar responses, regardless of whether
the load is aerobic or anaerobic [25].
Immediate and 5-min post-exercise measurements showed an increase in testosterone levels
both in men and women [26]. Acute exercise-­
induced testosterone increments are also seen in
older men [27]. This acute hormone response
was confirmed and described to be markedly
stronger in young men compared to old in a study
involving ten men with mean age 26.5 years and
ten men with mean age 70.0 years [28].
As muscle mass increases with strength
training [4] and is correlated with testosterone
112
levels, it could be expected that the testosterone
response to acute exercise is higher in persons
constantly involved in strength training.
Consistently, a 6-month sprint training program increased plasma testosterone concentrations in response to sprint exercise in adolescent
boys [23]. Experienced weight lifters compared to beginners showed similar basal levels
of testosterone but were able to evoke a stronger testosterone response during exercise [20].
Contrary to these findings, a long-term training
period of 12 weeks involving younger (mean
23 years) and older men (mean 63 years)
showed no significant results concerning testosterone levels before or immediately after
exercise [29].
Ronnestad et al. [30] investigated the effects
of testosterone and growth hormone (GH) transient increase during exercise, indicating that
performing leg exercises prior to arm exercises, thereby increasing the levels of testosterone and GH, induced superior strength training
adaptations compared to arm training without
acute elevation of hormones. It has been found
that acute elevation in endogenous testosterone
(by strength training) potentiates the androgen
receptor (AR) response to a strength training
session compared to no acute elevation of
endogenous testosterone [31]. It might thus be
speculated that the results by Ronnestad et al.
are due to an increased AR expression, and
through an improved testosterone-receptor
interaction, and a subsequent increased protein
synthesis, leading to superior strength training
adaptations. This hypothesis has also been
evaluated by Ahtiainen et al. [32], who have
described a correlation of individual pre- to
post-training changes in resting AR protein
concentration with the changes in cross-sectional area of muscle fibers in a combined
group of young and elderly subjects who performed heavy resistance exercise bouts before
and after a training period. Collectively, these
findings suggested that the individual changes
of AR protein concentration in skeletal muscle
following resistance training may have a critical impact on training-induced muscular
adaptations.
F. Lanfranco and M. A. Minetto
echanisms Underlying Increases
M
in Circulating Testosterone Following
Short, Intense Exercise
No conclusive and homogeneous evidence about
gonadotropin response to an acute exercise bout
is available. In fact, LH and FSH levels have been
reported to be increased, decreased, or unchanged
by short-term strenuous exercise [33–36].
The exercise-associated increment in circulating testosterone is considered not to be mediated
by LH, due to the inconsistent LH response and
to the evidence that testosterone levels increase
more quickly than LH in response to exercise.
Possible mechanisms such as hemoconcentration, reduced clearance, and/or increased testosterone synthesis may be involved [34, 36–38].
However, the timing of testosterone response differs from that of other circulating steroids (e.g.,
androstenedione and dehydroepiandrosterone
increase simultaneously with cortisol), thus suggesting that specific testicular mechanisms are
involved [36]. These mechanisms may include
the activation of the sympathetic system, which
stimulates testicular testosterone production during exercise via a direct neural pathway in some
species [39]. Catecholamine levels also increase
significantly during exercise. Beta-adrenergic
blockade inhibits testosterone responses to exercise, whereas L-dopa, phentolamine, and clonidine had no effect [40]. An anticipatory increase
in circulating testosterone levels has also been
described and seems to be independent of hepatic
perfusion or hemoconcentration [33, 36].
Ultimately, the exact mechanisms involved in
increasing testosterone concentrations in specific
exercise protocols are yet to be delineated.
rolonged, Submaximal Exercise
P
and Chronic Exercise Training
Decrease Circulating Testosterone:
From the “Female Athlete Triad”
to “Relative Energy Deficiency
in Sport (RED-S)”
In contrast to the short-term testosterone increment during and immediately after short, intense
7
The Male Reproductive System, Exercise, and Training: Endocrine Adaptations
113
exercise, a suppression of serum testosterone lev- rather seen between the so-called high and low
els occurs during and subsequent to prolonged responders. Each group has a specific endocrine
exercise, in the hours following intense exercise, reactivity pattern concerning the hypothalamus-­
as well as during chronic exercise training [10].
pituitary-­
adrenal axis [44]. It seems that the
During the last decades, an increasing number decrease of testosterone levels under the stressful
of investigative research studies have pointed to situations of endurance sport is not sufficiently
how chronic exposure to endurance exercise answered by the pituitary. There is no adequate
training can result in the development of a dys- rise in LH levels, which seem to be unaltered or
function within the reproductive components of even show a tendency to decrease with the growthe neuroendocrine system. The majority of these ing amount of stress impact. Nevertheless, age-­
studies have concentrated upon women. However, dependent effects seem to exist in this regard, and
the effects of endurance exercise training on the the ratio of androgen to estradiol is shifted by
male reproductive neuroendocrine system have physical activity to a more favorable pattern
been investigated beginning in the 1980s [41]. (higher androgen and lower estradiol levels) in
Most studies observed athletes during training older men compared to younger men performing
and competition, giving the impression of gener- regular mild physical activity [45].
ally lowered androgen levels, but lack the comParticipation in sports where leanness is conparison with a control group [9].
sidered a competitive advantage, such as running,
A controlled study examining the effects of cycling, wrestling, lightweight rowing, and gymendurance training on the hypothalamus-­ nastics, has been linked to lower body mass index
pituitary-­testis axis involved 53 men undergoing (BMI) [46], eating disorders [47], and low energy
endurance training for at least 5 years and a con- availability [48]. Low energy availability in the
trol group of 35 age-matched, sedentary men. context of anorexia nervosa has been associated
Baseline serum testosterone levels of the exer- with low testosterone levels in males [49].
cising men were significantly lower than in the Hagmar et al. [50] evaluated athletes from 26 difcontrol group. Differences in gonadotropins ferent sports and divided them into those who
were not seen. Normal regulation would require participated in leanness sports and those who did
LH levels to rise with falling testosterone levels, not. The leanness sport athletes had lower body
as these have a positive feedback on pituitary fat, higher spinal bone mineral density (BMD),
gonadotropin release. A suppression in the regu- lower serum-free testosterone and leptin, and
latory axis has been proposed as an explanation higher IGF-1 binding protein. The authors sugof this finding [42].
gested that the increase in BMD could be because
Contrary to these observations, basal testos- of the increase in mechanical loading in the speterone levels in trained weight lifters were not cific leanness sports, which presumably overaltered, nor did an increase in the daily training came the effects of lower testosterone and leptin,
volume change these levels [43]. Similarly, basal both of which are bone anabolic hormones.
testosterone, free testosterone, bioavailable tesFagerberg [51] has recently outlined the negatosterone, and sex hormone-binding globulin tive consequences of low energy availability in
concentrations were not significantly different in male bodybuilding. Bodybuilding is a sport in
high top-class athletes (sprinters and jumpers) vs. which athletes compete to show muscular definiuntrained subjects [22].
tion, symmetry, and low body fat. The process of
Endurance training can be seen as a factor of contest preparation in bodybuilding includes
exposure not only to physical but also to psycho- months of underfeeding, thus increasing the risk
logical stress. It has been demonstrated in a con- of low energy availability and its negative health
trolled study that the reactivity patterns of mental/ consequences, including extreme effects on cirpsychological and physical stress response of the culating testosterone levels.
hypothalamus-pituitary-adrenal axis are the same
In female athletes, low energy availability is
in a specific individual. Differential reactivity is a component of the female athlete triad, a term
114
used to describe the interrelationship of
decreased energy availability, subsequent
hypothalamus-­pituitary-­gonadal axis inhibition
leading to menstrual irregularity, and decreased
bone mineral density [48]. The triad was first
described by the American College of Sports
Medicine (ACSM) in the 1990s. In 2007, the
ACSM published a revised position stand on the
female athlete triad describing it more broadly
as the harmful effects of low energy availability
on menstrual function and bone mineral density
[52]. The International Olympic Committee
(IOC) has recently proposed an expansion of the
concept of the female athlete triad to include
males and has coined the term “relative energy
deficiency in sport (RED-S)” [53]. The development of the term RED-S had three main purposes: (1) to draw awareness to the fact that
energy restriction can have negative consequences in men in addition to women; (2) to
highlight other potential negative health and
performance consequences of low energy availability in athletes besides bone problems; and
(3) to encourage expansive research into the
potential myriad effects of low energy availability in various populations, including paralympic
athletes [10].
The “Exercise-Hypogonadal Male
Condition”: Clinical Issues
It has been demonstrated that among subjects
engaged in chronic exercise training, a selected
group of men develop alterations in their reproductive hormonal profile, i.e., persistently low
basal resting testosterone concentrations [54, 55].
In particular, the majority of these men exhibit
clinically “normal” testosterone concentrations,
but these concentrations are at the low end of normal range or even reach subclinical status. In
2005, Hackney and associates proposed the use
of “the exercise-hypogonadal male” as a label for
this condition [56].
The health consequences of such hormonal
changes are increased risk of abnormal spermatogenesis, male infertility problems, and compromised bone mineralization [54, 55, 57, 58].
F. Lanfranco and M. A. Minetto
Without large-scale epidemiological studies
in this area, clear prevalence data is not available
[59]. However, several studies show a clear and
consistently reduced serum testosterone concentration in highly aerobically trained individuals,
suggesting the exercise-hypogonadal male condition (EHMC) can be a common response [42,
59, 60]. It also appears that as the level of athlete
increases, so too does the incidence and severity
of the condition [61]. In addition, with no long-­
term data currently available, it is unclear
whether the presence of reduced testosterone
varies throughout a competitive season and how
long it takes for testosterone to return to normal,
if at all [59].
The time course for the development of the
EHMC or the threshold of exercise training necessary to induce the condition remains unresolved, but preliminary evidence suggest an
extended window of time (i.e., years) may be
necessary for its development [55] .
EHMC shares similarities with overreaching
or overtraining and has also been described in
male athletes as a parallel process to the female
athlete triad, with hypogonadism replacing
functional hypothalamic amenorrhea [62, 63].
The existence of the EHMC fits into the terminology of RED-S as clinical manifestation of it
may include sexual dysfunction like infertility
and reduced libido as well as reduced BMD
with associated increase in risk of bone stress
injury [59].
The “Exercise-Hypogonadal Male
Condition”: Pathophysiological
Mechanisms
Exercise-hypogonadal men frequently display
a lack of significant elevation in basal LH in
correspondence with the reduced testosterone
concentration, reflecting hypogonadotrophichypogonadism characteristics [41, 54, 64].
These LH abnormalities may involve disparities in luteinizing pulsatility (i.e., pulse frequency and amplitude), although evidence for
altered LH pulsatile release is conflicting [65,
66]. Moreover, gonadotropin response to
7
The Male Reproductive System, Exercise, and Training: Endocrine Adaptations
GnRH has been reported both reduced and
increased following prolonged, exhaustive
exercise [67, 68].
Exercise-hypogonadal men have been shown
to have altered basal PRL [54]. At either excessively low or high circulating levels, PRL can
result in suppression of testosterone levels in men
[69]. It has been speculated that the absence of
PRL at the testicle alters the effectiveness of LH
to stimulate testosterone production. This theory
is based upon the proposed synergistic effects of
PRL upon testicular LH receptors [41]. However,
not all investigators reporting low resting testosterone in endurance-trained men have reported
the concomitant existence of low resting PRL
levels [69]. Some investigations have looked at a
potential relationship between high PRL levels
and low testosterone, speculating that any “stressful” situation might provoke disproportionate
PRL responses in exercise-hypogonadal men and
this ultimately promotes a reproductive axis disruption [70].
As previously mentioned, leptin and ghrelin
are two hormones associated with appetite regulation which function as metabolic modulators of
the gonadotropic axis, as well [13, 71]. Acute and
chronic exercise can impact upon resting leptin
and ghrelin concentrations, independent of
changes in body adiposity [72, 73]. However, to
date no research studies have examined whether
leptin and/or ghrelin concentrations are altered in
exercise-hypogonadal men. Such work would be
illuminating on the topic and is needed.
Other research investigations have focused on
alterations in testicular ability to produce and
secrete testosterone and to respond to exogenous
stimuli (i.e., LH or hCG). Whereas animal studies have demonstrated that exercise training compromises testicular enzymatic activity [74], data
in exercise-hypogonadal men are contradictory.
In fact, some investigations suggest testicular steroidogenesis is normal, while some indicate it is
marginally impaired when challenged with exogenous stimuli [54].
Another potential disruptive hormone to the
gonadal axis is cortisol. Studies in a wide range
of sports (e.g., cycling, marathon running, football, handball, rugby, tennis, swimming, and
115
wrestling) have almost all shown increased cortisol concentrations during exercise [75, 76].
Cortisol secretion increases in response to exercise intensity and duration, as well as to the training level of subjects [77–80], at least in part to
mobilize energy stores. An inhibitory effect of
the hypothalamus-pituitary-adrenal axis on the
reproductive system has been demonstrated in
both sexes [81, 82]. In fact, glucocorticoids suppress gonadal axis function at the hypothalamic-­
pituitary level [81]. Moreover, Inder et al. [83]
have demonstrated that dexamethasone administration in humans reduces circulating testosterone and downregulates the muscular expression
of the AR. Finally, CRH and its receptors have
been identified in the Leydig cells of the testis,
where CRH exerts inhibitory actions on testosterone biosynthesis [84].
Interestingly, a sporting event and also training for such represent both a physical and a mental stress [9]. The release of cortisol by activation
of the hypothalamic-pituitary-adrenal axis as
reaction to mental stress is well documented,
especially in competitive situations [44, 85].
Stress responses by the hypothalamic-pituitary-­
gonadal axis are constantly found as well.
Along this line, anticipatory stress was measured in 50 males before a 1-day experimental
stress event (participation in stressful clinical
research protocol). Cortisol levels rose significantly, while both testosterone and LH secretion were decreased [86]. Psychological stress
markers as measured by scales for anxiety, hostility, and depression were correlated with
serum levels of testosterone in a group of males
aged 30–55 years. Those classified as highly
stressed had significantly lower testosterone
levels than their counterparts [87]. A cross-sectional study involving 439 males all aged
51 years showed those with low levels of testosterone (adjusted for body mass index) to exhibit
a cluster of psychosocial stress indicators [88].
Nevertheless, other hormonal profile studies
reporting the existence of low testosterone in
trained men did not show elevated resting cortisol levels suggesting that the hypothalamicpituitary-adrenal axis is not playing any role in
the development of EHMC [41, 59, 60, 89].
116
However, resting cortisol levels do not necessarily reflect a hyperactivity of the hypothalamus-pituitary-adrenal axis, which can be better
defined either by serial blood or salivary sampling [90] or by assay of urinary free cortisol.
Thus, at this time the role of cortisol to the
changes found in the gonadal axis of trained
men is in need of further studies.
ffects of Physical Exercise
E
on Spermatogenesis
Clinical expression of impaired reproductive
function in men engaged in chronic exercise
training seems uncommon [57, 66, 91].
However, chronic physical exercise may induce
a state of oligospermia, a reduction of the total
number of motile sperm and an increase in
abnormal or immature spermatozoa. Increase in
“round cells” has also been reported indicating a
possible infectious and/or inflammatory environment [57].
Arce and colleagues [57] were able to retrospectively establish an exercise (i.e., running)
volume threshold of 100 km/wk for semen alterations to occur, as they found alterations in sperm
density, motility, morphology, and in vitro sperm
penetration of standard cervical mucus in
endurance-­
trained runners when compared to
resistance athletes or sedentary subjects.
Similarly, Safarinejad et al. [68] observed a negative effect of training on sperm parameters in
high-intensity training athletes when compared
to moderate-intensity ones.
Scientific evidence seems to support the existence of a minimum level of volume for detrimental effects to take place, either hormonal or
seminological [54, 57]. As Hackney et al. [54,
56] highlight, alterations may well represent the
accumulative effect, more than the acute
response, of years of training load.
Some of the latest research has shown that
training intensity, and not only volume, is greatly
important in this equation as well. In fact,
Vaamonde et al. [92] point out that sperm DNA
damage and alteration are oxidative stress-related
parameters.
F. Lanfranco and M. A. Minetto
High-level athletes have been typically training for many years, making it difficult to establish a potential harmful training threshold
(volume and/or intensity) as they normally start
training at pre- or peri-pubertal years [93].
Nevertheless, high volume cycling training
seems to correlate with sperm morphology
anomalies. Wise et al. [94] have examined the
association between regular physical activity
and semen quality in a large cohort of 2261
men attending an infertility clinic. They found
that none of the semen parameters (semen volume, sperm concentration, sperm motility,
sperm morphology, and total motile sperm)
were materially associated with regular exercise. However, in the subgroup of men who
reported bicycling as their primary form of
exercise, bicycling at levels of >5 h/wk was
associated with low sperm concentration and
total motile sperm. These findings generally
agree with earlier studies that have shown deleterious effects of bicycling on semen parameters among competitive cyclists [91, 95]. It
remains unclear as to whether the changes associated with bicycling are due to mechanical
trauma (i.e., caused by compression of scrotum
on the bicycle saddle), to a prolonged increase
in core scrotal temperature (i.e., related to exercise itself or wearing of constrictive clothing),
or some other factors [96].
xidative Stress as a Putative
O
Mechanism Underlying Impaired
Spermatogenesis in Exercise-­
Hypogonadal Men
Several mechanisms have been reported to
affect the male reproductive function in exercising subjects. Alterations in the hormonal milieu,
as discussed in the previous paragraph, may
well play a role, since qualitatively and quantitatively normal spermatogenesis is critically
dependent on an intact hypothalamus-pituitarytestis axis. On the other hand, it has been
reported that endurance exercise is associated
with oxidative stress [97]. During endurance
exercise, there is a 10- to 20-fold increase in
7
The Male Reproductive System, Exercise, and Training: Endocrine Adaptations
whole body oxygen (O2) consumption, and O2
uptake in the active skeletal muscle increases
100- to 200-fold [98]. This increase in O2 utilization may result in the production of reactive
oxygen species (ROS) at the rates that exceed
the body’s capacity to detoxify them [99]. An
increase in the formation of ROS decreases fertility, as the ROS will attack the membranes of
the spermatozoa, decreasing their viability
[100]. Vaamonde et al. [101] have reported exercise-related alterations in sperm which may be
prevented with antioxidant agents. Vaamonde
et al. [102] also reported that, similarly to sperm
morphology, cycling volume positively correlates to sperm DNA fragmentation, also observing high correlation between training volume,
sperm DNA fragmentation, and percentage of
morphological abnormalities [93].
However, an increasing number of studies
suggest that exercise training enhances antioxidant capacity [103, 104]. Indeed, the machinery
eliminating ROS adapts after regular exercise
and actually lowers the amount of ROS that is
produced, especially in the major organs (muscles) of oxygen consumption and ROS production. In recent years, the anti-inflammatory and
antioxidant properties of regular exercise training have prompted some investigators to
explore the effects of different exercise modalities on markers of inflammation and oxidative
stress in seminal plasma [105, 106]. Hajizadeh
Maleki and colleagues have conducted independent randomized controlled trials looking at
the effects of exercise training at different
intensity levels on markers of reproductive
function and reproductive performance in infertile and fertile men and demonstrated significant improvements in a variety of sperm
oxidative stress and inflammation assays as
well as semen quality and sperm DNA integrity
following 24 weeks of exercise training, suggesting that regular resistance exercise, in particular at a moderate intensity level, positively
affects the markers of male reproduction [105,
107–109]. However, how changes in seminal
markers of male reproductive function may be
connected with reproductive outcomes remains
to be determined.
117
Conclusions
The male gonadal axis function is strongly
affected by physical exercise. Relatively short,
intense exercise usually increases, while more
prolonged exercise usually decreases serum
testosterone levels. Restricted energy availability may negatively affect hormone levels
both in female and in male endurance athletes
as highlighted by the definition of “relative
energy deficiency in sport (RED-S)” by the
IOC. Reduced or low-normal circulating testosterone concentrations involve health consequences such as an increased risk of abnormal
spermatogenesis, infertility problems, and
compromised bone mineralization. Thus,
awareness must be raised that exercise can represent a potential cause of andrological problems. On the other hand, moderate and
low-level exercise has been recently shown to
exert positive effects on the male reproductive
potential. Ultimately, additional research is
needed in this area with proper standardization
in assessment tools and study protocols to draw
more accurate conclusions about the effects of
physical exercise on the male gonadal axis
function.
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8
Exercise and the Hypothalamus:
Ovulatory Adaptations
Angela Y. Liu, Moira A. Petit, and Jerilynn C. Prior
Introduction
As early as 1939, Hans Selye, who later received
the Nobel prize for work on the endocrinology of
the adaptation response, reported that muscular
exercise was often a cause for “menstrual irregularities” in women [1]. Selye performed controlled animal experiments showing that whether
or not exercise suppresses reproduction depends
on the abruptness of exercise onset [1]. Forty
years later, Shangold et al. [2] published the first
prospective observational study documenting
gradual shortening of the luteal-phase length
with increased running activity in one woman
with regular menstrual cycles. Despite these early
observations indicating that subtle alterations of
ovulatory function occur within cycles of normal
length, the exercise science literature has since
focused on the absence (amenorrhea) or presence
(eumenorrhea) of menstrual flow in women athletes. The purpose of this chapter is to review the
A. Y. Liu
University of British Columbia, Medicine, Division
of Endocrinology, Vancouver, BC, Canada
M. A. Petit
Activ8, LLC, St. Paul, MN, USA
J. C. Prior (*)
University of British Columbia, Medicine, Division
of Endocrinology and Metabolism,
Vancouver, BC, Canada
e-mail: jerilynn.prior@ubc.ca
subtle but clinically important ovulatory changes
in response to exercise.
Hundreds of cross-sectional studies report
“athletic amenorrhea,“and inappropriately imply
causal relationships between loss of flow and
exercise. However, better-designed prospective
studies observing normally ovulatory women and
closely examining ovulatory function during progressively increasing exercise in reproductively
mature women (subsequently termed “exercise
training”) show only subclinical changes and no
amenorrhea when exercise training is the only
stressor [3–5]. Prevalent but subtle changes in
ovulatory function are the first and most subtle
hypothalamic adaptation to exercise training [2,
6]. Failure of hypothalamic adaptation in
response to intense stressors such as starvation,
psychological distress, illness, or rapidly increasing exercise results in significant disability.
Overwhelming stress associated with excessive
exercise training (see Chap. 9) and extreme nutritional imbalance (see Chap. 10) are discussed
elsewhere in this volume.
In this chapter, we describe the subtle alterations in ovulatory function that occur as a result
of hypothalamic adaptation to exercise training
and other “stressors.” We will also discuss the
consequences of ovulatory disturbances, including infertility and a negative bone balance. Before
beginning that discussion, however, it is necessary to define both the language and the physiological processes of ovulation.
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_8
123
A. Y. Liu et al.
124
The Ovulatory Cycle
The words used to describe the release of an egg
and the hormonal characteristics of a cycle in
which that occurs need to be defined and
described because both are usually obscured by
the pervasive, yet imprecise notion that regular,
normal-length cycles are always or usually normally ovulatory. We will start by defining the language of reproduction.
Terminology
In the exercise science literature, women are
commonly inappropriately classified as “eumenorrheic” (which means “true menstruation!”) if
their menstrual flow occurs monthly, or oligo/
amenorrheic if flow is sporadic or has been absent
for 3 or more months [7]. However, cycles of normal length need to also be described by their
postovulatory luteal phase or ovulatory characteristics. (Note that sometimes “anovulatory” is
inaccurately used to mean oligo-amenorrhea).
Ovulatory and cycle interval characteristics form
a complex continuum (Fig. 8.1). This starts with
the most normal cycle type, which is ovulatory
with a normal luteal-phase length of 10–16 days
(d) and a normal cycle length of 21–35 days [8].
This spectrum ends with the most disturbed ovarian function, which is amenorrhea, defined as the
absence of flow for 3 or more months. Between
these extremes, cycles that are normal in length
may have a short (<10 d) or insufficient (normal
length and estradiol levels, but low progesterone)
luteal phases, or be anovulatory (normal estradiol
but low progesterone levels). This latter is now
termed “subclinical ovulatory disturbances.”
Anovulatory cycles are ones in which cycle intervals may be short, normal, or long in length, but
no egg is released and progesterone levels never
meet or exceed 9.54 nmol/L (3 ng/mL) [9].
Fig. 8.1 A spectrum of
cycle types starting at
the top (I) with the most
normal, which is of
normal length and
ovulatory with a normal
luteal-phase length. The
next cycle (II) is also of
normal length and
ovulatory, but has an
insufficient but
normal-length luteal
phase. The third cycle
(III), also of normal
length, illustrates a short
luteal-phase cycle. The
fourth cycle (IV) is an
anovulatory cycle of
normal length, and the
final cycle (V) is an
anovulatory cycle that is
longer than normal in
cycle length
(oligomenorrhea)
I
II
III
IV
V
0
5
10
15
20
25
Days
Flow
Luteal phase
30
120
8
Exercise and the Hypothalamus: Ovulatory Adaptations
Definitions
Given the importance of clarity in science, it is
useful to define the terms meant to describe cycle
types when ovulatory status is not known.
Eumenorrhea implies menstrual cycles that are
normal in length, with flow occurring every
21–35 d [10]. When a woman’s flow occurs
between 36 and <90 d, the term oligomenorrhea
is appropriate. For cycle lengths of ≥90 d, women
are classified as experiencing amenorrhea. Cycles
of varying and abnormal lengths are called “cycle
disturbances”; cycles of normal length but short
absent or low progesterone levels are called “subclinical ovulatory disturbances.”
Cycles are defined as having short luteal-­
phase lengths if ovulation occurs, but the time
from ovulation to the day before the start of flow
(luteal phase) is<10 d by quantitative basal temperature analysis [8, 11] or <12 d using the midcycle urinary luteinizing hormone (LH) peak as
the indicator of luteal-phase onset. An inadequate or insufficient luteal phase means ovulation occurs and luteal-phase length is normal,
but peak progesterone levels in the luteal phase
are lower than usual (ideally ~45 nmol/L,
[14.3 ng/ml]). If ovulation and subsequent corpus luteal formation do not occur, the cycle is
anovulatory. Therefore, anovulation refers to
cycles in which no eggs are formed (and
released). “Subclinical ovulatory disturbances”
are cycles that are normal in length, but have
either short or inadequate luteal phases or are
anovulatory. Cycles that are irregular or abnormal in length and about which ovulatory characteristics are (usually) unknown should be termed
“cycle disturbances” and include polymenorrhea
(cycles shorter than 21 d) as well as oligomenorrhea and amenorrhea.
I mprecise Language About
Reproduction
Two terms are sometimes used that have problems
of precision: “eumenorrheic/eumenorrhea” and
“anovulatory/anovulation.” There are several
problems with classifying women as eumenorrheic. The term has been applied to women who
“experienced at least 10 menstrual periods per
year” [12], even though this would give an aver-
125
age cycle length of 36.5 d (which is abnormally
long) and that is oligomenorrhea. Another difficulty with the term, eumenorrheic or eumenorrhea, is that it presumes that all cycles of normal
length display the same ovulatory and hormonal
characteristics. Data from our 1-year prospective
study in ovulatory women of varying exercise
habits [4] showed that normal-length cycles could
as easily be anovulatory as ovulatory. In that
study, all of the anovulatory cycles were normal in
length. Therefore, a further erroneous assumption
often made in the literature is that only long or
short cycles are hormonally abnormal.
The term “anovulatory/anovulation” menstrual
cycle is also often misused. Researchers often
assume a woman is “anovulatory” if she reports
that her cycles are long or irregular—that may or
may not be the case. Likewise, the term “anovulation” is commonly used as a synonym for amenorrhea or oligomenorrhea because women whose
periods are long or have stopped (unless they have
become pregnant) are usually not ovulating.
In short, classifying women only by their cycle
intervals implies that the reproductive system
works in an on-off or mechanical manner, rather
than displaying the broad spectrum of potential
responses described above. Classification of
women’s cycles needs to include the entire range
of cycle and ovulatory types, because a distinctly
different hormonal profile is present in each case.
In addition, the variability and hormonal physiology of cycles, even those of normal length, are
important to understand.
Physiology
Just as cycles vary in interval and ovulatory characteristics, so does the cascade of signals from
the hypothalamic gonadotrophin-releasing hormone (GnRH) nucleus to the pituitary
gonadotrophin-­
producing cells. Pituitary messages to the ovarian follicle also change, as do
hormones from the ovary that give feedback to
the pituitary and the hypothalamus. What follows
is an effort to clarify the cycle manifestations of
the hypothalamic changes described in earlier
chapters (i.e., Chaps. 1 and 4).
126
varian Hormone Levels During
O
the Normal Cycle
An ovulatory menstrual cycle is characterized by
systematic and major changes in the levels of
estradiol prior to ovulation (follicular phase) and
variations of both estradiol and progesterone
post-ovulation (luteal phase). Follicular-phase
estradiol levels during and just after flow average
60–200 pmol/L (levels that are similar to those in
children and men). Estradiol levels subsequently
rise over the next 7–18 d to a peak just prior to
ovulation that is, on average, 220–250% above
the follicular-phase baseline [13]. There is then a
decrease to about 100% above baseline for most
of the luteal phase before estradiol levels again
decrease to low levels just prior to menstruation
[13]. In contrast, progesterone levels, which
remain low during the entire follicular phase
(~0.5–2.0 nmol/L, similar to levels in children
and men), increase after ovulation to over 1400%
of follicular-phase baseline values. Progesterone
levels produced by one corpus luteum remain
elevated over 1000% above baseline during the
10–16 d of the luteal phase [13].
The production of estradiol and progesterone
is coordinated by, and ultimately dependent on,
the timing and magnitude of GnRH pulsatility in
the hypothalamus. GnRH stimulates the gonadotrophins, LH, and follicle-stimulating hormone
(FSH), to be released from the pituitary. LH
peaks at midcycle, and directly triggers follicle
rupture and egg release. FSH plays an important
role in recruiting intermediate-sized follicles and
stimulating the dominant follicle that eventually
ovulates. In addition, FSH increases LH receptors on ovarian granulosa cells. GnRH, LH, and
FSH are all in feedback regulation by estradiol
and progesterone levels. Also, FSH production is
actively suppressed by inhibin, a polypeptide
hormone that is key in perimenopause [14] but
whose potentially important role in reproductive
physiology remains poorly understood [15].
ormonal Profile Changes During
H
Disturbed Cycles
Hormonal characteristics of cycles related to
their length will be briefly discussed followed by
the hormonal characteristics of cycles that have
A. Y. Liu et al.
disturbed ovulatory characteristics. Although few
studies have systematically measured estradiol
levels in cycles that are short or long, the generalization that shorter cycles have higher estradiol
levels is supported by a study in which hormone
levels were measured daily during 68 cycles [16].
That study documented that shorter follicular-­
phase lengths were associated with statistically
higher follicular and whole cycle estradiol levels
[16]. The logic of this observation is that the
more estradiol stimulation of the endometrium,
the more likely it is to shed causing bleeding. The
opposite is true of long cycles—less estradiol
stimulation of the endometrium leads to delayed
shedding and flow.
The hormonal characteristics of cycles with
disturbed ovulation are less clear. The common
feature of all disturbed cycles is the lower amount
and/or duration of progesterone production.
Estrogen and androgen productions are highly
variable in individuals with ovulatory disturbances. Evidence for high estrogen levels with
anovulatory cycles is most clearly found in studies of women shortly after puberty [17] and in
perimenopausal women [18]. In both instances,
estrogen levels exceed the midcycle peak equivalent levels for prolonged periods of time.
Androgen excess, which is associated with
anovulation, is also associated with high estradiol
levels [19], obesity, insulin resistance, and varying degrees of hirsutism.
Evidence that estradiol levels may be normal
in anovulatory cycles comes from our observational prospective study [4]. In that group of initially ovulatory women (in whom perimenopause
and androgen excess were excluded), the cycles
without ovulation were normal in length, and the
women who had entirely normal ovulation did
not differ in mean estradiol level (measured twice
in two cycles a year apart) from the women who
experienced anovulation. This flies in the face of
the expectation that cycles with disturbed ovulation will have low estradiol levels as had been
observed in four women studied by Sherman and
Korenman [20]. Sowers et al. also have reported
a few days of lower mid-follicular estradiol levels
in premenopausal women with disturbed ovulation [21]. However, several other authors in addi-
8
Exercise and the Hypothalamus: Ovulatory Adaptations
tion to ourselves have not observed consistently
low estradiol levels associated with anovulation
[22, 23]. By contrast, the estradiol levels were
minimally, although significantly lower in cycles
without progesterone levels above 9.54 nmol/L in
a single normal-length cycle study in over 3000
women in Norway [9].
In summary, disturbances of cycle interval are
often associated with abnormally low or high
estradiol levels (inversely related to cycle length),
but cycles with ovulatory disturbances may have
high, normal, or low estradiol levels and rates of
production.
Documentation of Ovulatory
Function
This section describes the currently available methods for documenting ovulatory function and the
advantages and disadvantages of each. Our primary
focus will be to describe the use of “Quantitative
Basal Temperature” (QBT), which we have found
to be the best available method for continuous, longitudinal monitoring of ovulatory function.
urrently Used Indirect Ovulation
C
Detection Methods
All of the currently available methods for assessing ovulation are indirect, except actual visualization of extrusion of a secondary oocyte from
the ovary. The closest to an indirect “gold standard” for ovulation is serial ovarian ultrasounds
observing a dominant-sized follicle that “disappears” because it has ruptured and released an
egg. Because ovulation requires an LH surge and
progesterone levels do not rise if ovulation does
not occur, serum or urinary measures of the midcycle LH peak and/or progesterone levels are
often used as indicators of ovulation. One method
is to perform serial samples of serum or urine
daily during the midcycle to detect the LH peak.
Alternatively, in the week prior to menses, serum
(or plasma) samples showing levels of progesterone of ≥9.54 nmol/L (≥3ng/mL) are indicative of
ovulation. The postovulatory increase in progesterone can also be measured in spots of whole
blood [24], urine, or saliva [25] or by its effect to
127
increase core temperature or to inhibit the stretch/
elastic characteristics of estrogen-stimulated cervical mucus (although this latter effect has not
been scientifically evaluated to date).
An estradiol peak is necessary to trigger the
midcycle LH peak. Therefore, another indirect
assessment of ovulation involves collecting estradiol levels daily with serum samples. Samples
must be taken until an estradiol level doubles the
preceding level and over 750 pmol/L (by usual
assays) is documented. However, midcycle peak
estradiol levels may occur and not be followed by
an LH peak or by ovulation in premenopausal (as
in perimenopausal) women [23, 26, 27].
Therefore, an estradiol peak level is not a specific
test of ovulation, nor is the stretch of cervical
mucus that estradiol stimulates. To a lesser
degree, the same lack of specificity is also true of
an LH peak [27].
imitations of Available Methods
L
for Diagnosis of Ovulation
Disturbances
Serial sampling of blood, saliva, or urine is
required to adequately document all of the important ovulatory characteristics (including whether
ovulation occurred, as well as luteal-phase adequacy and length) of a single cycle. Using these
methods to document several consecutive cycles
is very labor-intensive, invasive, expensive, and
imposes a high degree of burden on participants.
Continuous longitudinal documentation of hormone levels in large numbers of women is, therefore, virtually impossible to obtain using these
sampling techniques [3, 5, 27]. Similarly,
although formerly endometrial biopsy analysis of
histological change related to progesterone was
considered definitive for luteal-phase adequacy
and length, it has a ±2-d SD and is not useful
[28]. Finally, serial ultrasound assessments (to
show a growing follicular cyst that enlarges to
over 18mm and then disappears) are now considered the indirect “gold standard” indicator of the
occurrence of ovulation [25], but they lack convenience and reasonable cost for most studies.
The logical question is: why not measure ovulatory characteristics during one cycle and then
just monitor cycle intervals over the necessary
128
period of time? Could you not infer that the subsequent cycles, if they are regular and normal in
length, are similar in ovulatory status? That
would be an accurate strategy if women’s cycles
were as stable in ovulatory characteristics as they
are in cycle interval. However, ovulatory characteristics are highly variable over time within
women [4, 8, 29, 30]. For example, Hinney et al.
[29] documented “corpus luteum insufficiency”
by a late luteal-phase progesterone level below
25 nmol/L in 109 women of whom only 55, when
tested in the following cycle, continued to show
corpus luteum insufficiency. Likewise, 5 years
after our intensive monitoring of continuous
cycles for 1 year in 66 women, cycle lengths (in
≥3 cycles) correlated well with previous ones
(r = 0.68, P < 0.05). However, luteal-phase
lengths correlated considerably less well
(r = 0.39, P = <0.05) [30].
Furthermore, as this chapter will subsequently
document, ovulatory disturbances caused by
hypothalamic adaptation occur rapidly and as
quickly revert to normal ovulation. Thus, studies
that measure ovulatory characteristics in only a
few cycles or monitor cycles discontinuously
(such as every other or every fourth cycle) are not
likely to detect ovulatory disturbances (in general) and particularly not likely to document
those related to hypothalamic adaptation to exercise. That is especially true if cycle characteristics are documented only in the cycle before
exercise intensity is again increased, as has been
done in two prospective studies [3, 5].
At least 6 months of continuous sampling, in
which both ovulation and luteal-phase lengths are
assessed, are necessary to adequately characterize
a sedentary, weight-stable woman’s menstrual
and ovulatory characteristics [31]. In exercising
women, it is even more critical to provide a robust
baseline from which to examine potential changes
associated with exercise training. For all of these
reasons, a noninvasive, inexpensive, and “habitforming” method for documenting ovulatory
characteristics is necessary.
uantitative Basal Temperature (QBT)
Q
Daily basal (meaning first thing after wakening
in the morning, fasting, and when metabolism is
A. Y. Liu et al.
stable) oral temperatures (often referred to as
BBT) potentially allow continuous, longitudinal
research into ovulatory characteristics to be
conducted. High levels of progesterone during
the luteal phase increase the basal temperature.
This increase begins to be significant approximately 24–48 h after the LH peak [11]. A monophasic set of basal temperatures during one
cycle, in which our least-squares program
(Maximina®) detected no significant shift,
characterized an anovulatory cycle with progesterone levels that did not rise sufficiently to alter
temperatures. A biphasic cycle is indicative of
ovulation [8], and the day of the significant temperature shift can be used to define the onset of
the luteal phase [11]. In ovulatory cycles, the
increased progesterone levels raise the basal
temperature during the luteal phase by approximately 0.2–0.3 °C.
However, BBT was a clinical tool before it
was a research method. Therefore, the early studies utilizing BBT as a method of detecting ovulation had a number of problems, including that
women might take their temperature at different
times of day, women had difficulties reading or
shaking down the older mercury thermometers,
women were expected to plot their own temperatures as a graph (which often resulted in inaccuracies of graphing), and the temperature patterns
were evaluated for the presence or absence of
ovulation using non-quantitative methods and
often “eyeball” or equally nonreproducible methods [32]. Finally, even when more systematic
methods of assessing changes in temperatures
were described [33], insufficient data relating the
temperature shift to hormonal data were
available.
In our laboratory, these problems have been
resolved by better instruction of women about
what the factors in addition to fever that alter
the basal temperature (such as awakening earlier or later than usual, or being up in the night)
and providing a form on which to record these
factors. In addition, we asked women to take
their temperature with a digital thermometer
reading to two decimal places and to record
temperatures in a list, rather than plotting them
on a graph. We then devised and applied a
8
Exercise and the Hypothalamus: Ovulatory Adaptations
computer program (Maximina®) of leastsquare analysis to each cycle of temperature
data and showed it to be valid against the independently assessed serum LH peak (r = 0.88)
[11]. At the same time, we validated the “mean
temperature” method of Vollman [8, 11]. This
more scientific method we named “Quantitative
Basal Temperature”, so we could differentiate it
from the crude and unscientific BBT methods
used in the past.
Thus, we believe we have transformed the
previously inaccurate and unreliable BBT
method into a scientific tool for documentation
of ovulatory characteristics. Furthermore, it is a
method that can be easily taught, requires only
a relatively inexpensive and durable digital
thermometer, and is one that interested women
can and will consistently use [4, 34] for lengths
of time exceeding a year. Taking of basal oral
temperature quickly becomes a habit. However,
for this to happen, it does require the interest
and commitment of women and of those teaching them.
The major difficulty with widespread use of
the QBT method is its lack of accuracy in those
whose time of waking and sleeping is variable
(e.g., those on shift work, with small children, or
students—although it was robust to time of awakening in one study [35]). A simpler method, not
dependent on a stable life pattern, and requiring
less commitment from women, is needed for documentation of ovulatory characteristics in longitudinal studies and for epidemiology.
Hypothalamic Adaptation
and Ovulatory Function
The neuroendocrine physiology of adaptation
to exercise and other stressors is complex and
not yet completely understood. A review article published more than 10 years ago continues
to reflect our current understanding on the subject [36]. It has also been covered by earlier
chapters in this volume, and therefore will be
reviewed only briefly here. The hypothalamus
functions to maintain internal homeostasis in
response to internal and external factors.
129
Numerous influences, such as ambient and
core temperature changes, energy balance
changes, illness (which alters eating and sleeping patterns and may cause elevated temperature levels), and psychological stress, can
directly or indirectly alter the pulsatile secretion of GnRH and thus change subsequent
reproductive function [36].
The premise of this chapter is that the first
and most subtle adaptive responses to exercise
training occur during the premenstrual phase
of the cycle with a range of ovulatory disturbances (Fig. 8.1) that all result in decreased
total exposure to progesterone. As discussed,
studies that examine hypothalamic control and
the subtle changes that lead to shortening of
luteal-phase length with exercise training
require long-term, continuous monitoring of
ovulatory function.
Ovulatory disturbances in response to exercise
training can be viewed as an adaptation to the
increased physiological and perhaps psychological stresses of the exercise and are not part of a
disease process. The adaptation model suggests
these four principles:
1. Ovulatory disturbances are caused by a hypothalamic process that is conservative, e.g.,
protective of or saving energy for the
individual.
2. They are induced by a variety of physical and
psychological “stressors,” which act through a
common mechanism and manifest similar
changes.
3. There are gradients of change in response to
the severity or intensity of the “stress” or
“threat.”
4. The adaptive changes reverse to the normal
baseline steady state when the “threat” is lessened or eliminated, or the individual has sufficient time and is able to adapt.
Evidence for these points will be described in
the following sections. The specific ovulatory
adaptations to exercise training, including the
gradients of change and reversibility, will be
described in the section “Adaptations to Exercise
Training” of this chapter.
A. Y. Liu et al.
130
Hypothalamic Adaptive Processes
Evidence that the subtle alterations that lead to
shortening of luteal-phase length are controlled
by the hypothalamus is largely circumstantial,
because altering hypothalamic function biochemically or with direct nerve cell stimulation is
impossible in humans. The strongest evidence
that the hypothalamus controls changes in ovulatory function comes from the similar pattern of
responses during exposures to a whole range of
psychological and physiological stressors.
Corticotrophin-releasing hormone (CRH)
discharge increases when any internal or external environmental signal is perceived as stressful (as shown schematically in Fig. 8.2). The
increased CRH may either directly or indirectly
(via the β-endorphin system) slow the hypothalamic pulsatile release of GnRH [38] and,
therefore, decrease pulsatile LH release.
Fig. 8.2 Processes
through which physical
(including exercise and
illness), emotional, or
nutritional challenges
cause increased release
of CRH from the
hypothalamus. These
factors suppress the
reproductive system and
stimulate the adrenal
axis. ACTH
corticotrophin; LH
luteinizing hormone.
(Modified from Prior
[37])
Because the pulses of LH stimulate estradiol
and androgen secretion, they provide an essential precursor to ovulation.
A systematic review by Hakimi and Cameron
[39] on the effect of exercise on ovulation proposed mechanisms by which vigorous exercise
disrupted ovulation in women with normal and
low body mass index, and by which exercise
restores ovulation in overweight and obese
women. They describe a U-shaped association of
exercise with ovulation: increases in ovulatory
disturbances with increased exercise especially
in women or normal or lower weight but decreases
in (pre-existing) ovulatory disturbances with
exercise in overweight women. This is based on
ten interventional and four observational cohort
studies, which showed that greater than 60 min
per day of heavy exercise was associated with an
increased risk of anovulation, while vigorous
exercise of 30–60 min per day was associated
Threats/stresses:
• Physical
• Emotional
• Nutritional
• Overtraining
Corticotrophin-releasing
hormone(CRH)
?
↑ β-endorphin
(neurotransmitters)
LH pulse
frequency
↑ ACTH
Subclinical ovulatory
disturbances
• Anovulation
• Short luteal phase
↑ Cortisol
↓ GnRH
Cycle disturbances
• Amenorrhea
• Oligomenorrhea
Normal estradiol
↓ Progesterone
Accelerated bone loss
↓ Estradiol and
↓ Progesterone
8
Exercise and the Hypothalamus: Ovulatory Adaptations
with a reduced risk of anovulation. Seven studies
examining exercise in overweight and obese
women with polycystic ovarian syndrome found
that exercise was associated with improved ovulatory function. Notably, one limitation in these
studies is the lack of assessment of rate of
increase in exercise intensity. Many of the cross-­
sectional studies simply observe current exercise
duration and intensity. Evidence documents that
the rate of progression of exercise training is an
important modulator as well [1, 40].
Reproductive and primarily ovulatory changes
are “conservative” for the individual, because
through multiple pathways, they effectively prevent pregnancy when the woman is unable to
physically or emotionally support a healthy process. They are also conservative of energy
because less progesterone production, which
decreases the otherwise increased core temperature, means women can consume about 300 fewer
dietary calories and, like women with normal
ovulation, still ensure energy balance [41].
131
In humans, reversible, modulated suppression of reproduction during illness was documented by lower than normal LH levels in
gravely ill, hospitalized postmenopausal
women; LH levels recovered as they improved
[45]. Similarly, a prospective study in Japanese
nursing students showed regular and apparently
ovulatory cycles with more frequent ovulatory
disturbances during the stressful school year
than in the summer break [46].
Weight loss is known to be one of the most
powerful physiological hypothalamic stressors
[47, 48]. An experimental protocol involving
fasting for 3 d in the late follicular phase appears
to be more disruptive of follicle development and
more likely to suppress LH pulsatility in women
who are initially very lean than in those who have
normal body weights and fat [49].
Active women with amenorrhea, like over-­
trained athletic men [50], have increased basal
levels of cortisol [51] and blunted cortisol
responses to exercise [52, 53]. Berga et al. [52]
reported high 24-h cortisol levels in those with
Stress Mechanism
hypothalamic forms of oligo-/amenorrhea comSelye [1] observed about 70 years ago that the pared with normally menstruating women. This
adrenal glands were hypertrophied when various hypercortisolemia was not observed in women
kinds of stressors interrupted estrus in rats. He with other reasons for disturbed cycles, such as
also observed similar patterns of response of the hyperandrogenism or hyperprolactinemia. A few
ovaries and the adrenals to excessive exercise, to women initially deemed to have hypothalamic
interference with normal diet, and to emotional amenorrhea subsequently ovulated during the
stressors. More recently a strong relationship was study and were shown to have concomitantly
also documented between social stress and non-­ reduced levels of cortisol [52]. Ding et al. [51]
ovulation in nonhuman primates. Subordinate could similarly predict women whose cycle interfemale monkeys experienced 16.5% of cycles as vals would subsequently become normal because
non-ovulatory, whereas dominant females over their cortisol excretion was decreased.
the same time period and in the same conditions
High cortisol secretion or urinary excretion
experienced only 3.5% of their cycles as anovula- has become a useful marker of hypothalamic
tory [42].The subordinate monkeys at autopsy adaptive responses to stressors including exerhad very enlarged adrenal glands [42]. Cortisol cise, because all stressors apparently act through
excess, which was similar to levels seen in the hypothalamic CRH pathway. Therefore, studwomen under stress, significantly increased the ies in both humans and nonhuman primates demmetabolic clearance of progesterone as well as onstrate increased cortisol levels simultaneously
increasing LH pulse amplitude in experimental with decreased LH pulsatility and/or disturbed
studies by Kowalski et al. [43]. This research ovulatory
function
during
reproductive
showed that monkeys who were exposed to ­disturbances coinciding with a variety of stressinduced hypercortisolism had lower luteal-phase ful situations.
serum progesterone levels and more ovulatory
It should be noted that, although hypothalamic
disturbances [43, 44].
disturbances of ovulation characterized by lower
A. Y. Liu et al.
132
pulsatile release of LH are probably the most
common cause for the menstrual cycle disturbances reported in athletes, short luteal-phase
cycles or an ovulation associated with androgen
excess (and with high, rather than low, LH levels)
[54, 55] can also be documented. High androgen
and LH levels have been described in swimmers
with amenorrhea [54]. In addition, defects of the
large corpus luteum cells have been postulated to
cause lower luteal-phase progesterone levels,
although LH pulsatility and estradiol levels are
both normal [29].
Energy Conservation
Reversible cycle disturbances are termed “functional” (that implies psychological) and are not a
disease. When discussing ovulatory disturbances
as protective against excess energy expenditure,
the severity of the disturbance is proportional to
the amount of energy conserved. Amenorrhea in
women without an extreme eating disorder may
be relatively less threatening than anorexia,
because compared with menstruating women, it
appears to lower BMR only 17% [56].
Anovulatory cycles, which are normal in length,
are also less metabolically costly to maintain
than ovulatory cycles and prevent the risk of
pregnancy with its high-energy demands. The
basal temperature increase during the luteal
phase raises metabolic rate. Barr et al. [41] documented that women’s dietary intake was increased
approximately 300 kcal/d during the hormonally
confirmed luteal phase of cycles compared with
anovulatory cycles in the same group of women;
all were without exercise or weight changes during the six-cycle study [41].
A shortened luteal-phase length (in contrast to
anovulation) occurs in response to the least
threatening intensity or kind of stressor. Energy
demands are higher when the luteal-phase length
is shortened than they are in anovulatory cycles,
due to up to 9 d of progesterone-related temperature elevation in the former. We believe that
shortening of luteal-phase lengths is the most
common adaptive response to stressors, such as
weight loss, emotional stress, illness, or exercise
training. It is of importance that, despite the minimal alteration of ovarian physiology, fertilization
and implantation of the egg are still prevented by
subclinical short luteal phase and luteal insufficient cycles.
ynergism or Interactions Among
S
Factors Influencing Ovulatory
Function
The concept of adaptation with a common hypothalamic change caused by many different stressors implies that the response to one, such as
exercise, would depend on the current state of
other factors, such as energy balance or emotional stress. Therefore, it is important to consider those factors that are known to influence
ovulatory function and to acknowledge that individuals may respond differently to any given
stress depending on the presence of many personal variables. The adaptive response is altered
by such factors as the individual’s current energy
balance, underlying characteristics of the individual (i.e., levels of reproductive maturation,
weight, and emotional well-being), intensity of
the threat, and the rapidity with which it is introduced. Multiple emotional and psychological
stressors, weight loss or restrictive eating, and the
need to feel “in control” all are often perceived as
stressful by the hypothalamus and influence
reproductive function (Fig. 8.3). These stressors
all appear to act through the common hypothalamic CRH pathway.
Energy Balance
It is likely that exercise and other stressors affect
LH pulsatility through their influence on energy
balance [57]. Other chapters in this volume discuss this (see Chaps. 11 and 17). We postulated
in 1982 that hypothalamic insulin receptors
might provide a common signal [6]. Those who
are ill or over-exercising would have decreases
in their insulin levels as a consequence of negative caloric balance. It is well accepted that
severe weight loss or an extreme energy deficit,
such as with anorexia nervosa, suppresses reproductive function. In such extreme cases, CRH
8
Exercise and the Hypothalamus: Ovulatory Adaptations
133
Emotional stress/threats
Need to feel “in control”
Hypothalamic-gonadal suppression
Compulsive exercise
Stress
fractures
Increased
musculoskeletal
injury
Binge/purge
syndrome
Cognitive
dietary restraint
↓ Estradiol and
↓ Progesterone
Weight loss
Infertility
↓ Libido
Ovulatory disturbances
Fig. 8.3 Interrelationships among multiple factors
(stress, compulsive exercise (associated with an increased
risk for relative energy deficiency), and cognitive dietary
restraint) that appear to be causally related to the development of ovulatory disturbances
levels are high [58] and amenorrhea will likely
result. More subtle reproductive disturbances
often occur when the relative threat is less
intense, but the conditions that facilitate pregnancy are still not optimal. For example, ovulatory disturbances may occur with healthy weight
loss or dieting [59], as well as when recreational
exercise or emotional stress increase. In each
case, the greater the need for energy conservation, the more severe the ovulatory or cycle
length disturbance [48, 60].
In 2014, Mountjoy et al. as part of an
International Olympic Committee Expert
Group presented the concept of relative energy
deficiency in sport (RED-S) (Fig. 8.4). This is
a more physiological and comprehensive alternative to what was called the “female athlete
triad” that refereed only to athletic women
[61]. RED-S is a syndrome characterized by
impaired physiological function in areas such
as metabolic rate, reproductive function (that,
for women means menstrual cycle and ovulatory changes), bone health, immunity, protein
synthesis, and cardiovascular health. It is due
to an imbalance between dietary energy intakes
relative to energy expenditures; when expenditure exceeds intake, this results in a relative
energy deficiency. The syndrome of RED-S is
applicable to both women and men and takes a
physiological rather than a disease approach to
the multitude of changes related to exercise
training.
The magnitude of energy deficit affected the
frequency of menstrual cycle and ovulatory disturbances in healthy women [63]. The average
percentage of energy deficit, in a study of
untrained, regularly cycling and ovulating women
aged 18–30 y followed over four menstrual cycles,
was the major predictor of the frequency of menstrual cycle/ovulatory disturbances even when
adjusted for weight loss. Luteal-phase disturbances, although they only vaguely defined their
documentation, were the most frequently observed
reproductive changes. However, there were no
differences by the degree of relative energy insufficiency in the development of anovulatory cycles
or oligomenorrhea [63]. When these authors
defined energy availability as energy intake minus
A. Y. Liu et al.
134
Immunological
Menstrual
function
Gastrointestinal
Triad
Cardiovascular
Bone health
RED-S
Endocrine
Psychological*
Growth +
development
Metabolic
Hematological
Fig. 8.4 Potential health effects of relative energy deficiency in sport (RED-S). This is applicable to both men
and women athletes. Note that ∗Psychological conse-
quences may precede or result from RED-S. (Modified
from [61] and the concept adapted from the original idea
of N. Constantini [62])
exercise energy expenditure divided by kilograms
of lean body mass and looked for associations
with ovulatory disturbances in 91 exercising
women, they found it discriminated clinical menstrual status (e.g., amenorrhea vs. regular menstrual cycles) but not subclinical ovulatory
disturbances [64]. This, again, highlights the distinction between menstrual cycle length changes
that are clinically obvious and the silent and more
prevalent ovulatory disturbances.
Cognitive Dietary Restraint
Subtle ovulatory disturbances also occur with
cognitive dietary restraint (also called “eating
restraint”), a psychological attitude in which
women feel they must limit food intake to avoid
obesity. Women who are classified as highly
restrained (based on the Three Factor Eating
Questionnaire [65]) are very conscious of their
food intake, but they do not necessarily consume
8
Exercise and the Hypothalamus: Ovulatory Adaptations
135
fewer calories than weight- and age-matched ponectin; and decreased triiodothyronine and kiscontrols who are not restrained [66, 67]. Because speptin [72]. Progesterone therapy in an RCT in
maintaining or achieving their desired weight is menopausal women caused a small but signifiso important to their emotional well-being, eat- cant increase in the level of free T4 [73].
ing is associated with psychological stress for Collectively, these changes appear to suppress
women with cognitive dietary restraint. A very the hypothalamic–pituitary–ovarian axis in an
early study using the Eating Restraint Scale of adaptive, graded manner [72].
the Three Factor Eating Questionnaire showed
It is probable that the effect of cognitive
that women with higher scores were more likely dietary restraint on ovulatory function is medito have short luteal-phase cycles [68]. Three ated through hypothalamic adaptation pathways.
studies from our laboratory also examined ovula- The evidence that subtle ovulatory disturbances
tory function and eating restraint in normal are more common among those with greater cogweight, regularly cycling, and ovulatory women nitive dietary restraint, despite similar energy
who varied in their usual activity levels [69] and intakes and expenditures, emphasizes that hypoin regularly cycling vegetarian and non-­ thalamic ovulatory disturbances may result from
vegetarian women [70]. A more recent study in relatively minor psychological as well as physiyoung adult women (most of whom were post-­ ological stressors.
secondary students) showed that those with
higher eating restraint scores had more ovulatory
disturbances and higher 24-hour urine-free corti- Hypothalamic Reproductive
sol levels [71]. The frequency of subclinical ovu- “Maturation”
latory disturbances and the degree of cognitive
dietary restraint were associated with less posi- Another variable influencing the ability of the
tive changes in bone mineral density, although hypothalamic/pituitary/ovarian system to respond
cortisol did not appear to modulate that relation- to stressors is its relative maturity. For example,
ship [71]. In all of these studies, the Restraint the majority of menstrual cycles are anovulatory
Scale of the Three Factor Eating Questionnaire in the first year after menarche [8]. However, on
[65] was administered initially, and menstrual average, women do not develop the highest rate
cycle characteristics were documented prospec- of ovulatory cycles until they are approximately
tively over three or six cycles or 2 years, respec- 12 years after menarche [8] (or gynecologic age
tively. In all studies, women in the highest versus 12). This implies that some are still gynecologilowest tertile of restraint were significantly more cally immature. It fits with the adaptation hypothlikely to experience a short luteal phase or anovu- esis that those whose hypothalamic–reproductive
latory cycle. These findings could not be attrib- axis has not yet become sturdily and regularly
uted to differences in energy intakes, exercise ovulatory are more likely than those with mature
levels, or body mass index (BMI is weight in kg reproductive patterns to respond to stress with
divided by height in m2) levels. Women with eat- altered cycle lengths as well as with ovulatory
ing restraint did not differ in BMI, weight, energy disturbances [46].
intake, activity levels, or cycle lengths from the
One of the first studies documenting the reproless restrained women in each respective popula- ductive hormonal characteristics of young athtion [69–71]. Since cycle intervals were unal- letes showed that both swimmers and controls
tered, none of these women would have known had short luteal-phase cycles, but in swimmers,
their ovulation was disturbed.
the luteal phase was even shorter than in ­sedentary
Changes in metabolic hormone levels have controls [74]. Although participant numbers were
been documented related to resting energy expen- small, these data confirm the more extensive data
diture. Metabolic alterations include growth hor- of Vollman [8] that teenagers are susceptible to
mone resistance and reduced IGF-1 concentrations; subtle disturbances of ovulation. Young runners
increased cortisol, ghrelin, peptide YY, and adi- (gynecologic age <10 year, mean chronologic
A. Y. Liu et al.
136
age 20 year) are also more likely to have disturbed folliculogenesis and decreased estradiol,
progesterone, gonadotrophins, and testosterone
levels than are gynecologically mature women
(gynecologic age >15 year, mean chronological
age 31 year) [75]. Therefore, data suggest that the
combination of more intense training and an
immature hypothalamus are potentially additives
in suppressing reproduction in young women.
Mature gynecological aged women who begin
exercise or intensify training only experience
ovulatory and not cycle-length changes. However,
evidence suggests, although we do not yet have
appropriate experiments to document it conclusively, that a woman in her 20s who is initially
only intermittently ovulatory and begins to exercise or intensifies exercise training may well
develop cycle as well as ovulatory disturbances.
This young woman, with weight loss or emotional distress added to exercise training, would
likely develop oligomenorrhea or amenorrhea.
Evidence says that age at menarche is influenced by the energy imbalance related to intense
exercise training [76–78]. Although genetic factors also have a strong influence on menarcheal
age [79], dancers and gymnasts who experience
lower energy availability are more likely to have
delayed menarche compared with their sedentary
sisters even though they are genetically very similar. Puberty involves maturation of axillary and
pubic hair as well as breast enlargement and areolar/nipple maturation. Interestingly, when young
athletes are forced (often because of injury) to
interrupt their gymnastics or dance training, rapid
development through one or more of the Tanner
breast stages commonly occurs [78, 80].
Anorexia nervosa commonly occurs in women
and during puberty. Weight loss and young age
may make them more vulnerable to anorexia. In a
similar manner, they will likely be more prone to
exercise effects on ovulatory function, especially
if exercise is combined with restricted energy
intake or psychological performance pressure
from coaches and parents. It is also probable that
women experiencing reproductive and ovulatory
disturbances in response to stress when younger
will be more susceptible to exaggerated stress
responses throughout life [81].
The pubertal maturation of the breast is primarily dependent on ovarian hormones, with little or
no influence of adrenal steroids. By contrast, pubic
hair maturation can proceed with the normal adolescent increases in adrenal androgen secretion,
without significant increases in ovarian hormones.
Discrepancy in the degree of Tanner stage breast
compared with pubic hair maturation is probably a
clue to hypothalamic adaptive changes related to
exercise training and/or other stressors. Warren
et al. [78] reported that pubic hair development
occurred at a normal age in young women dancers,
but there was a trend to delays in breast development and age at menarche. Clinical data from
ovarian hormone treatment of male-to-female
transgender individuals [82] and observations during a prospective study of puberty [83] both suggest that normal breast development to the fully
mature Tanner stage V breast will not be reached
without adequate exposure to ovulation and thus to
high progesterone levels.
tress Intensity and the Rate
S
of Increase in Stress Intensity
Whether ovulation becomes disturbed partially
depends on the intensity of the stress and partly
on the rate of introduction of that stress. For
example, in one study all rats responded to “inescapable” shock by suppressed gonadotrophin
secretion [84], whereas only some rats were susceptible to the relatively less threatening stress of
gradually increased endurance exercise [1].
Hans Selye coined the term “general adaptation syndrome” and published early controlled
trials of exercise and energy restriction stress
on rats [1]. Selye’s experiments showed a dramatically different response to gradually
increasing exercise compared with rapid imposition of exercise training (or caloric restriction) (Fig. 8.5). Animals which started running
at 3.5 km/d ­developed anestrus (the rat equivalent of amenorrhea) with interstitial atrophy,
few mature follicles, and increased weight of
their adrenal glands. A second group of rats
gradually increased exercise intensity to reach
3.5 km/d over 4 weeks (Fig. 8.5). Even though
8
Exercise and the Hypothalamus: Ovulatory Adaptations
Fig. 8.5 Illustration of
the concept of the
“general adaptation
syndrome” developed by
Hans Selye. Exercise
was introduced abruptly
or gradually in rats
randomized to one or the
other group. The
photomicrographs show
ovulatory adaptation by
normal interstitum and
follicular development
in rats with gradual
increase in exercise.
Abrupt introduction of
exercise led to anestrus
(the rat equivalent of
amenorrhea), interstitial
atrophy, and development
of only a few mature
follicles. (Data redrawn
from Ref. [1])
137
Exercise
Abrupt
Gradual
30.5 cm wheel
20 r.p.m.
Initial
15 min - 3 x day
0.86 km/day
60 min - 3 x day
3.5 km/day
2 weeks
30 min - 3 x day
1.7 km/day
”
4 weeks
60 min - 3 x day
3.5 km/day
”
Normal estrus
Anestrus
OVARY
at 3 mo.
Normal interstitium
the rats in the second group maintained the
same level of exercise intensity as the first
group for 2 of the 3 months, reproductive function remained normal, and ovarian follicle
development was appropriate. Similar differences in response were observed in rats treated
with rapid “semi-starvation” compared with
gradual decreases in caloric intake [1]. Selye
subsequently showed a similar pattern of reproductive response in restrained rats as those separated from their cage-mates or siblings. These
data suggest that similar mechanisms of hypothalamic adaptation on the reproductive system
occur in response to exercise training, weight
loss, and psychological stress as well as to illness [45].
In Selye’s day, before immunoassays for hormones were available, the level of stress was best
indicated by adrenal gland weights. Because
reproductive disturbances occurred in parallel,
they were also assessed as “adaptive” and related
Interstitial atrophy
to a generalized stress response. These observations are consistent with current data showing
elevated cortisol levels in women with hypothalamic disturbances of ovulation, oligomenorrhea,
and amenorrhea [85].
These classical animal stress experiments are
only now being reproduced in humans. However,
as will be discussed in more detail below, the data
available in mature women suggest that a high
training intensity and volume is well tolerated if
adequate nutrition and a suitable time for adaptation to that exercise are allowed.
Finally, although interactions among “treat”
or “stress” variables had been postulated in
women [6], it has not been experimentally documented. One very important prospective, controlled experimental study in female cynomolgus
monkeys has shown that there are synergistic or
added reproductive system effects of psychological “stresses” on top of metabolic or energy-­
related threats [86].
138
Adaptations to Exercise Training
Exercise Training Studies
in Reproductively Mature Women
Only a few studies have prospectively documented changes in cycle and ovulatory characteristics as with exercise training in mature women.
The first prospective documentation, in only one
woman, used the elasticity of cervical mucus as a
marker of the midcycle estradiol peak to show
shortening of the luteal phase associated with an
increase in weekly running distance [2]. Other
early studies showed an increased prevalence of
short luteal phase or anovulatory cycles associated with increasing intensity or volume of exercise training [87, 88]. In a group of 14
reproductively mature women (gynecologic age
>15 year, mean chronologic age 35 years) who
had been training for a marathon, only one-third
of a total of 48 cycles prior to a marathon (three
cycles/woman) were ovulatory with normal
luteal-phase lengths [88]. The only difference
between nonovulatory and ovulatory cycles
appeared to be the length of the usual training run
from approximately 2–5 miles [88].
A study of longer duration (14–15 month) in
women not initially proven to be ovulatory
showed a decrease in the volume of menstrual
blood and lower estradiol levels with marathon
training [89]. Running activity increased from 24
to 100 km/week over the study period. Ovulatory
characteristics were not examined, however, and
the inclusion of participants from ages 24 to
57 years old [89] confounds these outcomes.
Nevertheless, in that study, and in none of the
others to be subsequently described, did the
women develop amenorrhea, despite rapid
increases in running activity/intensity mandated
by some of the protocols.
In Table 8.1 we compare three important prospective studies of exercise and reproduction.
These studies have all sought to establish an
influence of exercise training on the reproductive
hormonal characteristics of both the follicular
and the luteal phases of the menstrual cycle as
well as ovulatory changes during exercise training: Bullen [27, 90], Bonen [3], and Rogol et al.
A. Y. Liu et al.
[5]. Because of their importance to this discussion, each study is described in detail below.
Bullen and colleagues [27, 90] monitored 28
college-aged women residing at a summer camp
by measuring hormonal characteristics for 2
cycles using analysis of daily overnight urines
and evening temperatures. These women (whose
mean age was 20 years) were confirmed to be
ovulatory prior to entry into the study and were
also randomly assigned to either weight-loss or
weight-maintenance groups. Running activity
increased from 4.5 to 10 miles/d by week 5 of the
8-week camp. In addition to running 10 miles/d,
women also participated in 3 h/d of varied recreational activities. Bullen and colleagues documented that none of the women in the study
developed amenorrhea despite their young age
and that they were exposed to several stressors,
including change of residence, intense and rapidly increasing exercise training, and caloric
restriction (in the weight-loss group). Ovulatory
disturbances and shortened luteal-phase cycles
were common, however, and only 8 of the 28
women ovulated normally in both cycles. The
addition of weight loss to the exercise training
caused a further significant increase in ovulation
disturbances as well as oligomenorrhea in a few
women [27, 90].
Bonen and colleagues [3] set out to determine
whether a dose–response between running mileage/week and reproductive function was operative. In particular, by observing sedentary, mature
women who ran at varying exercise loads, they
tried to determine whether or not a threshold of
exercise intensity was present above which
luteal-phase disturbances would begin. Bonen [3]
monitored mature women over 2–4 month who
were variously training at <16, 16–32, or
32–48 km/week. These investigators showed that
although there were trends toward shortening of
the luteal phase in the first cycle measured after
training began, no consistent luteal-phase length
changes were documented, nor were there any
differences in ovulatory characteristics between
women in different intensity groups [3].
A study by Rogol et al. [5] was similar to
Bonen’s, but used VO2max testing to document
the anaerobic threshold or when lactate began to
8
Exercise and the Hypothalamus: Ovulatory Adaptations
139
Table 8.1 Published prospective studies of exercise training on menstrual cycle and luteal phase lengths
Author
Bullen et al. [27]
Bonen [3]
Rogol et al. [5]
28
57
23
Total (n)a
Chronologic age 22 (0.6)
30.0 (1.3)
31.4 (1.3)
Gynecologic age 10 (0.6)
17.1 (1.4)
17.8 (0.9)
Train at lactate threshold
<10 miles/week for
Mean (SE) Study Exercise + weight maintenance (A)
(n = 9)
2 months (A)
groups
Exercise + weight loss (B) (max of
Train above lactate
<10 miles/week for
−0.45 kg/week)
threshold (n = 8)
4 months (B)
10–20 miles/week for
2 month (C)
10–20 miles/week for
4 months (D)
20–30 miles/week for
2 months (E)
20–30 miles/week for
4 months (F)
Duration of
2 months
2–4 months
1 year
exercise training
As described above
Start: 6.25 miles/week
Exercise
Running 4 miles/d progressing to
Weeks 1–20: add
schedule
10 miles/d by week 5, plus 3.5 h of
1.25 miles every second
cycling, tennis, or volleyball
week
Weeks 20–39: hold at
24 miles/week
Weeks 40–end: add
1.25 miles every second
week (max of 40 or
65 miles/week)
Exercise intensity 70–80% of max aerobic capacity
Not reported 6 d/week ran
(adjusted each month)
at lactate threshold
3 d/week ran at lactate
threshold and 3 d/week ran
above lactate threshold
Sampling method Daily BBT and daily urinary
Daily blood samples
Daily blood samples day 9
sampling (overnight)
through end of cycle
Sampling
Continuous
Every second cycle
Every fourth cycle
intervals
Mean LL not available cycle types
Control
Mean LL
Cycle 1
Mean LL
Luteal length
during training
cycle
14.2 (1.5)
13.9 (0.6)
(LL)
Mean (SE)
Study group
A
B
Run cycle 1 12.6 (1.0)
Cycle 4
13.4 (0.7)
Cycle 8
13.8 (0.7)
%Ovulatory
25
6
Run cycle 3 14.2 (1.5)
(only
includes
groups B, D,
and F)
%Short luteal
66
63
Cycle 12
12.8 (0.7)
phase
%Anovulatory 42
81
Detrain,
12.1 (1.3)
cycle 3 or 5
NA
NA
Additional
Young gynecologic age
stressors
Weight loss
Away from home Intense exercise
training
a
Number of participants who completed the study
140
be produced. This assessment was used to gradually increase the exercise intensity to maintain
physical activity just below or above the “lactate
threshold.” This allowed investigators to more
accurately document the exercise load, which
was gradually increasing over 1 year. Participants’
hormone levels were intensively sampled every
4 months before the next increase in exercise
intensity. Rogol et al. [5] also reported that neither running intensity nor duration affected ovulatory function in women training for 1 year at
increasing intensities that were maintained either
above or below their own adjusted lactate
threshold.
Several differences exist between the studies
of Bullen and those performed by Bonen and
Rogol, which at least partially explain their discrepant outcomes. The rapid introduction of a
high volume of training and the addition of
weight loss in Bullen’s protocol provides a
greater stress load and would thus be more
likely to lead to ovulatory disturbances than an
exercise program alone in older women who
remained in their own homes and communities
[3, 5]. In addition, the women in Bullen et al.’s
[27] study were significantly younger in both
chronological and gynecological ages. Another
important difference is in design—Bullen and
colleagues increased exercise intensity rapidly,
whereas the other two studies were more gradual in exercise intensification. Finally, these
studies differ in the methods and time course of
monitoring. Bullen et al. [27] monitored cycles
consecutively and inclusively. In contrast,
Bonen and Rogol et al. assessed ovulatory characteristics intermittently every two or every four
cycles, respectively. Shortened luteal-phase
length or anovulatory cycles may have been
missed because monitoring occurred after one
or three cycles of probable adaptation to a new
exercise load. Any ovulatory disturbances would
have likely occurred in the first cycle following
the increase in training volume. By the second
or fourth cycle after the increase in intensity/
duration of training, adaptation would have
occurred, homeostatic balance would be
achieved, and normal ovulatory function would
have returned.
A. Y. Liu et al.
We, like Bullen et al. [27], have monitored
luteal length and ovulation continuously, but over
1 year in 66 community-dwelling women of varying self-chosen activity levels [4]. As described
earlier, all women were confirmed to be normally
ovulatory on two consecutive cycles prior to study
entry. Despite that, over 80% of the women experienced at least one short luteal phase or anovulatory cycle during the year of study. When the
average cycle, luteal phase, and two cycles of hormone levels were used, no differences were found
by exercise habit in the number or severity of ovulatory disturbances, or in estradiol and progesterone levels. That was true regardless of whether
the women were completing <1 h of aerobic exercise/week (normally active controls), running
more than 1 h/week, but not training for a specific
event (consistent runners), or runners increasing
training in preparation for a marathon that 19
women completed during the study year [4]. The
reason for the subclinical ovulatory disturbances
that did occur was not initially understood.
However, we have subsequently found them to be
more prevalent in women scoring high on the
Restraint Scale, suggesting they are related to
cognitive dietary restraint [69–71].
The same study was recently used to compare
the characteristics of the pre-marathon cycle in
the marathon-training women with a season-­
matched cycle in the consistent runners. Exercise
training without weight loss can be shown to
cause shortening of the luteal phase. The luteal-­
phase characteristics of the cycle before the marathon were compared in marathon-training
women with their own initial and final cycles and
the pre-marathon cycle with a season-matched
middle cycle from the consistent runners.
Compared to both their own cycles during less
intense training and all of the cycles in the consistent runners, significant shortening of the
luteal-phase length before the marathon occurred
in the marathon-training women (Petit & Prior,
Personal communication, 2010).
Hypothalamic adaptation to the runners’ baseline exercise probably had occurred before they
passed the screening for two consecutive ovulatory cycles and became qualified to enter the
study. However, the intensified training before
8
Exercise and the Hypothalamus: Ovulatory Adaptations
the marathon appeared to cause shortening of the
luteal phase in the cycle prior to the marathon
when their training mileage was the greatest. The
detailed dietary, weight, body fat, and hormonal
characteristics also monitored before the marathon are being studied for explanations other than
exercise training to explain the luteal-phase
shortening that was documented. These data all
suggest that adaptation to increased exercise,
even as intense as training for a marathon, normally occurs with only shortening of the luteal
phase in well-nourished, reproductively mature
women who have no major emotional distress
[91]. In addition, as discussed below, adaptation
allows a woman’s reproductive system to show
rapid shortening of the luteal phase and equally
rapid reversion to normal.
bservable Changes Prior
O
to Ovulation Disturbances: Molimina
Prior to shortening of the luteal-phase length,
which is the first objective change in reproductive
function, other observable but even more subtle
changes are commonly reported by mature women
who are beginning exercise training. The earliest
change with moderate, recreational levels of exercise is a decrease in molimina [92] as recorded by
the daily Menstrual Cycle Diary© [37] (available
at www.cemcor.ca). “Molimina,” whose Greek
etymology means “the work of bringing on flow,”
includes the set of physical and emotional, but not
troublesome, indicators of the coming menstrual
flow. Although premenstrual symptoms may occur
in both ovulatory and non-ovulatory cycles [93],
we previously believed that molimina indicated
that ovulation had occurred. However, a recent
large study in over 400 unselected women could
not confirm the molimina/ovulation association.
However, it did show, in the few women who
observed it, a highly ovulatory cycle-specific
development of axillary breast tenderness during
the week before flow [94].
An additional indicator of an ovulatory cycle
is the disappearance of elastic or stretchy cervical
mucus after the midcycle estrogen surge. Because
progesterone inhibits cervical production of elas-
141
tic mucus, this time pattern of the presence and
then the disappearance of mucus is also a potential indicator that ovulation has occurred.
We asked whether exercise would decrease
premenstrual experiences by studying a group
of proven ovulatory women runners who were
increasing their exercise training over 6 months.
Exercise training was associated with decreased
fluid symptoms and decreased feelings of
depression despite no changes in weight or
cycle characteristics [92]. Age and weight
matched non-exercising and ovulatory women
studied in parallel experienced no significant
changes in premenstrual experiences over the
same study period [92].
Time Course of Ovulatory Adaptation
With the addition of more strenuous training,
endocrine changes progress to a shortened luteal
phase. The next and more disturbed cycle is
anovulatory. This sometimes occurs a straining
workload increases [6]. The sedentary woman
whose training and cycle characteristics are
shown in Fig. 8.6 developed severe back pain
during the 12th cycle and did not ovulate. It is
likely that she developed anovulation because
she not only had to deal with the stress of the pain
but also what for her was an important worry that
she would be unable to compete in and finish the
marathon for which she had trained so hard.
In a woman with well-established normally
ovulatory cycles (probably after gynecological
age 12), exercise-training adaptive changes do
not normally progress to anovulation. However,
if an additional stressor is added, such as illness,
insufficient energy intake, weight loss, and/or
emotional stress (see sections “Exercise Training
Studies in Reproductively Mature Women” and
“Reversibility/Adaptation” in this chapter),
anovulation may develop. Amenorrhea will
­usually not develop unless the woman is of young
gynecologic age, is not yet sturdily ovulatory,
and has stresses in addition to exercise training,
such as eating restraint or psychological stress,
energy imbalance, rapid induction of exercise, or
rapid weight loss.
A. Y. Liu et al.
142
Reversibility/Adaptation
A few within-person studies are useful to illustrate further the progression and reversibility of
ovulatory adaptation. Figures 8.6 and 8.7 show
luteal-phase lengths as documented by QBT [91]
for 1 year of consecutive cycles in two mature,
normal-weight women. One of these women, as
discussed above, was a sedentary woman who
trained for and ran a marathon during the year of
observation (Fig. 8.6). The other was a rather
lean and compulsive runner who wanted to
become pregnant (Fig. 8.7) [91]. The first woman’s prospective record indicated alternating
cycles showing short luteal-phases (<10 d) and
normal luteal-phase lengths with anovulation
during the cycle before and of the marathon race.
As mentioned above, the pain and worry of an
injury as well as exercise training likely accounted
for anovulatory cycles. A normal luteal-phase
length cycle returned when both her emotional
stress and her training workload decreased immediately after her successful marathon.
Figure 8.7 shows prospective documentation
of ovulatory characteristics over 1 year in another
woman who was running regularly, but was quite
lean and stressed. She showed consistently short
luteal-phase cycles early in the year. In an effort
to reverse her secondary infertility, she decreased
running for one cycle, but this was emotionally
stressful. Her secondary infertility was due to
inadequate or insufficient luteal-phase characteristics documented by endometrial biopsy. When
she stopped running for approximately 6 weeks,
she became pregnant.
These detailed case histories of two women
who monitored their individual exercise and
ovulatory characteristics over an extended period
Follicular phase
Injured
Luteal phase
Marathon
*
Anovulatory
*
35
30
9
11
11
8
9
12
11
25
7
8
9
13
15
7
Miles run/day
20
5
Days
12
10
3
5
1
9 10 11 12 13 14
1
2
3
4
5
6
7
8
Sequential menstrual cycle number during marathon training
Fig. 8.6 This bar graph, illustrating cycle lengths as bars
and luteal-phase lengths as blue areas within those bars,
shows sequential menstrual cycles and ovulation during
1 year of marathon training in a previously sedentary
woman. Note the alternating short and normal luteal
phases and progression to anovulatory cycles (in cycles
#12 and #13) just after the most intense and highest mile-
age of training just before and in the marathon cycle. The
arrow shows injury which caused her to decrease training
and major emotional stress that likely contributed to the
anovulatory cycle. When she decreased her training following the marathon, ovulation and her luteal-phase
lengths were restored to normal. (Modified from Ref.
[91])
8
Exercise and the Hypothalamus: Ovulatory Adaptations
143
Follicular phase
Endometrial
Luteal phase
biopsy
Pregnancy
30
8
10
8
8
25
9
8
6
8
8
8
20
9
Miles run/day
8
Days
7
15
6
10
8
4
6
4
2
2
0
9
10 11 12
1
2
3
4
5
6
7
8
Sequential menstrual cycle number during marathon training
0
Fig. 8.7 This bar graph is similar in format to Fig. 8.6
and shows the sequential menstrual cycle and ovulatory
characteristics in a woman who was training intensely
and compulsively. Even with decreased running during
the first few cycles, she continued having short lutealphase cycles. Endometrial biopsies (arrows) were consis-
tent with luteal-phase deficiency. In the middle of cycle
11, she stopped running and became pregnant before a
normal luteal phase could be documented. She carried the
child to term and delivered a healthy baby. (Modified
from Ref. [91])
of time indicate the rapid hypothalamic adaptation and reversibility of ovulatory disturbances
related to exercise training [91]. These data have
since been supported in larger samples of women
runners [4, 88].
Very few data clearly document adaptation to
exercise over longer than a year. As an example,
it is useful to observe the second marathon-­
training year in the woman whose cycles before
and after her first marathon were documented in
Fig. 8.6. Her cycles and ovulatory characteristics
before her second marathon a year after her first
are shown in Fig. 8.8. During the first marathon,
she had shown short luteal-phase cycles progressing to anovulatory cycles the month prior to
(M-1) and of (M) the marathon. In her second
marathon, 1 year later, luteal length remained
normal throughout her training, although her
training was similar in volume and intensity to
her earlier marathon. It appears possible that by
the second year, she had adapted to the marathon
training, which allowed her cycles to maintain
normal ovulation. Key in each of these stories is
the fact that the woman was basically emotionally healthy and maintained normal body weights,
and good energy intakes avoiding relative energy
deficiency (Fig. 8.4).
In mature women, adaptation to exercise training with reversal to normally ovulatory, normal-­
length cycles commonly occurs within one cycle.
These adaptive changes of luteal-phase length
with increasing exercise training are modeled in
Fig. 8.9. Note that, as in the woman described
above who trained for her first marathon, by the
end of the year, the model suggests that a level of
exercise intensity that had provoked ovulatory
A. Y. Liu et al.
144
5
0
M-2
Anovulation
10
Anovulation
Luteal length (days)
15
M-1
M
M+1
Marathon 1
Marathon 2
10
Miles/cycle day
Fig. 8.8 Luteal-phase
lengths during the cycles
before and just after a
marathon in the first
marathon training and
race (as shown in
Fig. 8.6) and in
subsequent marathon a
year later. During the
second marathon,
despite similar or
increased mileage, there
were no luteal-phase
disturbances
documented. This
illustrates reproductive
adaptation to the levels
of exercise this woman
was now performing.
(Modified from Prior
et al. [95])
5
0
M-2
disturbances now no longer causes a change from
a normal ovulatory cycle.
Bullen’s study [27] also demonstrated rapid
reversibility when training ceased. Although a
few women developed oligomenorrhea as well as
disturbances of ovulation, all of the women
regained both normal cycle intervals and normal
ovulatory function within a few months after the
end of the summer training camp. Furthermore, it
is common for athletic women to become pregnant within months of decreasing their training
(and loss of competitive stress), even though they
may have had several years of anovulatory cycles
or amenorrhea [91, 96, 97]. However, in exercising younger women, in whom the hypothalamus
M-1
M
M+1
has not fully matured, the return to or achievement of normal ovulatory cycles will often take
longer.
Although the majority of the data just presented were collected using QBT analyses
many years ago, no studies since have closely
examined ovulatory characteristics continuously during several months of exercise training. The development of new methods of
monitoring ovulation and luteal-phase length,
for example, with salivary progesterone [25],
should soon allow the nuances of cycle adaptation to be more specifically characterized and
mechanisms and modulating factors more carefully delineated.
8
Exercise and the Hypothalamus: Ovulatory Adaptations
Vo2
max %
Exercise
intensity
A
80–90
4 hours week
5
80
3 hours week
4
70
2 hours week
60
1 hour week
50
0.5 hour week
0
145
B
C
E
D
F
3
2
1
Sedentary
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
3
4
5
6
7
8
9
10 11
Consecutive menstrual cycles
12
13
14
15
Luteal length (days)
16
12
8
4
0
1
2
Fig. 8.9 Theoretical model of the luteal-phase changes
that occur over time with increasing exercise in an ovulatory woman who is undergoing exercise training. Note
that at the end of the year’s sequence of cycles, despite a
considerable exercise load, luteal-phase length and ovulation are normal. (Modified from Prior et al. [95])
Clinical Applications/Treatment
If ovulatory disturbances are documented, it is
very easy to provide physiological treatment.
Evidence suggests and the Centre for Menstrual
Cycle and Ovulation Research recommends that
persistent ovulatory disturbances should be treated
by prescribing either cyclic oral micronized progesterone (300 mg at bedtime) or medroxyprogesterone (10 mg) on days 14–27 of the woman’s own
cycle [34, 99] (http://www.cemcor.ca/resources/
cyclic-progesterone-therapy).
Although this “treatment” does not directly
correct the hypothalamic stressor(s) or energy
insufficiency that led to the disturbance in the
first place, feedback to the hypothalamus by progesterone may aid in reproductive maturation and
ovulatory recovery. The most useful function of
cyclic progesterone is to provide physiological
levels of progesterone, which will cause regular
The practical and clinical implications of ovulatory adaptation to exercise training are not
the purpose of this chapter. However, it is
important that the clinician and coach be alert
to document persistent disturbances of lutealphase length or any anovulatory cycles because
we now know they are associated with significant bone loss [98]. These ovulatory disturbances, if observed, are very useful indicators
that the exercise training load is excessive for
that woman’s level of hypothalamic reproductive maturation and/or when combined with
other potentially present stressors, e.g., competitive anxiety, insufficient caloric intake,
moving away from home, weight loss, eating
restraint, or even illness.
A. Y. Liu et al.
146
0.1
Spinal bone density (L1-L4)
1
1 year change (g.cm2- )
DXA
DXAe
0.05
0
-0.05
-0.1
A
n = 16
B
n = 16
C
n = 15
D
n = 14
Fig. 8.10 This dot-plot figure shows individual rates of
1-year spinal bone mineral density change by dual-energy
X-ray absorptiometry (DXA) in 61 active, healthy,
normal-­weight women ages 20–35 with amenorrhea, oligomenorrhea, subclinical anovulation, or subclinical short
luteal phases stratified by reproductive status and randomized to receive medroxyprogesterone acetate (that acts
through the osteoblast progesterone receptor) cyclically
for 10 d/cycle (10 mg/d of MPA) with or without active/
calcium therapy (1000 mg/day) or placebo. Women in A
were taking cyclic MPA plus calcium; B cyclic MPA plus
placebo; C placebo MPA plus calcium; and D double placebos. The effects of cyclic MPA were highly significant
(P = 0.0001), and calcium was borderline (P = 0.07).
There was a significant 2.0% loss of bone in the double-­
placebo (D) control group [34]
menstrual flow if estradiol levels are normal and,
acting through the osteoblast progesterone receptor (PR), will increase bone mineral density
(BMD) [100]. Cyclic medroxyprogesterone
­(acting through the osteoblast PR) in a randomized, placebo-controlled 1-year trial caused a significant 2% increase in spinal areal BMD in
mild-­
moderately active women with hypothalamic disturbances of cycles or ovulation
(Fig. 8.10) [34]. Although combined hormonal
contraceptives (CHC) are the usual therapy for
“functional” hypothalamic amenorrhea or oligomenorrhea, in adolescent women, CHC may
cause skeletal [101] and reproductive [102] harm.
CHC therapy for treatment of hypothalamic
amenorrhea has also been associated with significantly lower rates of recovery (42%) and slower
recovery than in women who declined any therapy [103].
The most important reason for the clinician or
coach to know about ovulatory disturbances is to
recognize them as adaptive and reversible and to
teach each woman to observe and understand the
menstrual cycle and ovulatory changes she may
experience. In this era of “self-help medicine,”
keeping the Menstrual Cycle Diary©, QBT (both
free at www.cemcor.ca), and training records will
increase self-knowledge and thus well-being for
health-conscious women.
Conclusions
This chapter has reviewed the subtle adaptations
of women’s reproductive system to gradually and
appropriately increasing exercise training.
Evidence suggests that decreases in luteal-phase
progesterone production and duration (subclinical ovulatory disturbances) are the first and the
major adaptive responses of the hypothalamic–
pituitary–ovarian system in mature women to
increasing exercise intensity. More obvious
changes in cycle lengths may occur if the relative
energy insufficiency of sport is also present or if
8
Exercise and the Hypothalamus: Ovulatory Adaptations
the exercise-training woman is within 5–10 years
of menarche. If no additional stressor other than
the exercise is present, the subclinical ovulatory
disturbances will reverse to normal within the
next cycle, even though the exercise training level
is maintained.
These physiological and psychological
changes during exercise training are protective
for the individual, are reversible, and cause no
long-term harm. However, if subclinical ovulatory disturbances persist (any anovulatory
and ≥ 2 short luteal-phase cycles/year) [4],
despite clinically normal cycles, bone loss occurs
[4, 98]. In addition, fertility is impaired by silent
ovulatory disturbances. Persistence of these ovulatory disturbances may be commonly related to
the psychological stress caused by cognitive
dietary restraint [71] and psychosocial stressors
related to women’s inferior cultural status [86].
The benefits of exercise for cardiovascular [104],
skeletal [105], and emotional health [106] are
well supported by scientific evidence, yet the
concept persists that exercise causes women to
develop amenorrhea which is an important negative reproductive event.
In this chapter, and as described in the concept
of relative energy deficiency in sport [61], we
have attempted to erase that perception by viewing women’s responses to exercise training as
adaptive. When increasing levels of exercise are
introduced gradually and energy balance is maintained, adaptation can occur, and the result is a
minimal change. Ovulatory disturbances occur
normally when initiating a more intense training
program or increasing exercise load, but will
reverse rapidly to normal once adaptation has
occurred. When taken to an extreme or combined
with other psychological (including cognitive
dietary restraint) or physiological stressors, exercise can cause definite negative reproductive
changes. In that circumstance, persistent ovulatory disturbances occur, which, depending on the
age, nutritional state, and emotional support of
the woman, may progress to oligomenorrhea or
amenorrhea.
Amenorrhea, although it is uncommonly associated with exercise in mature, ovulatory women,
may occur in the face of exercise combined with
147
a negative energy balance or when several stressors coexist, especially in women who have not
established
regularly
ovulatory
cycles.
Gynecological immaturity is a significant factor
impairing the ability of women to appropriately
adapt to exercise stress. This implies that caution
should be taken in the progression and sequence
of increasing exercise intensity in young
athletes.
In summary, although the concept of adaptation to exercise training has been known for
almost 70 years [1] and has been applied to women’s reproduction since the 1980s, few well-­
controlled studies have documented the subtlest
evidence of this adaptation: subclinical ovulatory
disturbances.
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106. McCann L, Holmes DS. Influence of aerobic exercise
on depression. J Pers Soc Psychol. 1984;46:1142–7.
9
Adrenergic Regulation of Energy
Metabolism
Michael Kjær and Kai Lange
Introduction
During exercise, energy turnover increases and
adrenergic mechanisms play an important role
in this regulation. In addition, increased adrenergic activity during exercise also results in an
increased heart rate and in an enhanced force of
myocardial contraction as well as in vasoconstriction in the splanchnic circulation, in the
kidneys, and in noncontracting muscles. These
circulatory changes favor a redistribution of
blood flow to exercising muscle as well as an
increased cardiac output [1]. Furthermore, the
adrenergic activity stimulates sweat glands and
thereby influences thermoregulation, and it
causes an increased contractility of skeletal
muscle as well as influences exercise-induced
suppression of components of the human
immune system. In the present chapter, it is
demonstrated how adrenergic activity can influence substrate mobilization and utilization
both directly and indirectly via secretion of
hormones.
M. Kjær (*) · K. Lange
Department of Clinical Medicine,
Bispebjerg-Frederiksberg Hospital,
Copenhagen, Denmark
e-mail: michaelkjaer@sund.ku.dk
drenergic Responses to Acute
A
Exercise
Adrenergic activity can be assessed both by
direct measurements of electrical activity in
superficial sympathetic nerves and by measurement of circulating norepinephrine and epinephrine in the blood. The direct recording of
sympathetic activity can be performed to resting
muscle only, but during exercise of, e.g., the
arms, sympathetic activity to the resting leg
muscle has been shown to increase with progressively increasing intensity of arm exercise
[2]. In addition to these measurements, a correlation has been found between sympathetic
nerve activity and plasma levels of norepinephrine [3]. Although a correlation between circulating norepinephrine and direct recordings of
sympathetic nerve activity from the peroneal
nerve has been demonstrated during exercise,
the increase in sympathetic outflow to the various regions of the body differs somewhat during
exercise. During exercise, using methods to
measure norepinephrine spillover, it has been
demonstrated that the increase in sympathetic
activity during exercise is dominated by an
increased sympathetic activity directed toward
active muscle. During two-­
legged exercise,
approx. 50% of all circulating norepinephrine is
released from sympathetic nerve endings in
active muscle. Furthermore, when arm exercise
is added to leg exercise, the norepinephrine
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_9
153
154
spillover from active leg muscle also increases
despite unchanged work output and unchanged
blood flow to the leg muscles [4].
In addition to norepinephrine released from
sympathetic nerve endings, epinephrine is
released from the adrenal medulla in response to
sympathetic neural activity during exercise. The
circulating epinephrine is responsible for the
major adrenergic effect on energy metabolism
during exercise compared with norepinephrine.
In the present chapter, the adrenergic effect on
carbohydrate and fat metabolism will be discussed, but epinephrine per se has been shown
also to increase protein metabolism in isolated
electrically stimulated rat muscle [5].
The levels of circulating free norepinephrine
and epinephrine increase with exercise intensity
expressed by the percentage of maximal individual performance (%VO2 max). This holds
true both during prolonged exercise and in
response to short-term intermittent exercise and
to intense weight training. The increase in
plasma norepinephrine and epinephrine occurs
rapidly in arterial blood, and it has been calculated that the half-life of epinephrine is around
2–3 min during exercise. Circulating levels of
catecholamines can only be considered as overall markers of sympathoadrenergic activity and
are influenced not only by secretion but also by
clearance of the hormone. Whereas clearance of
norepinephrine is difficult to determine on a
whole-body level owing to the fact that it is
extracted at two levels in series, namely, both
the lung and the systemic organs [6], the turnover of epinephrine can be studied in humans,
using a radio-labeled tracer. It has been shown
that whole-body clearance of epinephrine
increases by 15% at low exercise intensities and
decreases around 20% below basal levels after
more intense exercise [7]. However, since the
increase in plasma epinephrine seen during
dynamic exercise in humans is five- to tenfold,
these changes are caused by increases in secretion from the adrenal medulla rather than by
changes in clearance. Among the major contributors to epinephrine clearance are the hepatosplanchnic area and the kidneys.
M. Kjær and K. Lange
otor Control and Reflex Influence
M
on Adrenergic Response
In experiments using partial neuromuscular
blockade to weaken the muscle force and thereby
increase the motor center activity needed to produce a certain force output, it was found that
exercise-induced increases in levels of circulating catecholamines were augmented compared to
control experiments with saline infusion [8].
These findings are supported by experiments in
paralyzed cats where direct stimulation of the
subthalamic locomotor areas in the brain resulted
in adrenergic hormonal responses similar to the
ones seen during voluntary exercise [9]. Together,
these experiments support the view that motor
center activity can directly stimulate sympathoadrenergic activity during exercise directly and
independently of feedback from contracting muscle. That central factors linked to exercise intensity are not sufficient to elicit a maximal
adrenergic response can be demonstrated in different ways. When exercising a small muscle
group (e.g., one knee extensor) even at maximal
intensity, only a small catecholamine response
can be observed [4]. Furthermore, when maximal
work output was reduced by more than 60% with
a neuromuscular blockade (tubocurarine), despite
subjects working at the highest possible effort,
adrenergic responses were far from maximal
[10]. In addition to central factors, peripheral
neural feedback can be demonstrated using lumbar epidural anesthesia in doses sufficiently high
to block impulses in thin afferent nerves but preserving motor nerves and the ability to perform
exercise to the highest possible degree. During
static exercise, but not during dynamic exercise,
catecholamine responses were inhibited when
afferent responses were absent [11, 12].
Interestingly, both ACTH and β-endorphin
responses during submaximal exercise were
abolished during epidural anesthesia [11, 13]. In
support of a role of afferent nerves in adrenergic
responses, plasma catecholamines increased in
response to direct stimulation of these nerve
fibers in cats [14]. An alternative model to study
feedback mechanisms during exercise is to use
9
Adrenergic Regulation of Energy Metabolism
patients with metabolic deficiencies. Both in
myophosphorylase (McArdle’s disease) and
phosphofructokinase deficiency and in mitochondrial myopathy, an excessive neuroendocrine response and exaggerated mobilization of
extramuscular substrate (glucose and free fatty
acid (FFA)) were found, most likely a coupling
toward the oxidative demands of the muscle cell
rather than to the oxidative capacity of the working muscle [15–17].
drenergic Activity After Physical
A
Training
Vigorous endurance training will reduce the catecholamine response to a given absolute workload [18], whereas neither sympathetic nerve
activity nor norepinephrine levels at maximal
workloads differ between individuals with different training status [19]. This supports the view
that physical training does not alter the capacity
of the sympathetic nervous system, but that
responses to submaximal exercise are linked
closely to the relative rather than to the absolute
workload [20]. Surprisingly, however, it has in a
24-h study been found that highly trained individuals had a higher catecholamine release over
the day compared with sedentary individuals
[21]. Epinephrine response in trained individuals
vs. sedentary has been shown to be enlarged
when stimulated by a variety of stimuli, such as
hypoglycemia, caffeine, glucagon, hypoxia, and
hypercapnia [20, 22–25]. This indicates that the
capacity to secrete epinephrine from the adrenal
medulla improves with training. In rats that
underwent 10 weeks of intense swim training, the
adrenal medullary volume and the adrenal content of epinephrine were larger in trained rats
compared with controls who were either weight
matched, sham-trained, or cold-stressed [26].
Although these findings indicate that the
improved secretion capacity of epinephrine is a
result of training, this will most likely require
several years of training. In well-trained athletes
who underwent hypoglycemia before and
4–5 weeks after an injury that resulted in inactiv-
155
ity, epinephrine responses did not change with
this short-lasting alteration in activity level [27].
However, still it is interesting that endocrine
glands apparently are able to adapt to physical
training and alter their secretion capacity, similar
to other tissues like muscle and heart.
Hepato-splanchnic Glucose
Production and Adrenergic Activity
During intense exercise the rise in hepatic glucose production was parallel with a rise in plasma
catecholamine levels [28–30]. In addition, in
models where electrically induced cycling was
used in spinal cord-injured individuals with
impaired sympathoadrenergic activity, hepatic
glucose production was abolished [31].
In swimming rats, the removal of the adrenal
medulla reduced the hepatic glycogenolysis
[32], as well as the exercise-induced increase in
hepatic glucose production in running rats [33].
However, most studies have been unable to
demonstrate any effect of epinephrine on liver
glycogen breakdown during exercise [34–37].
In running dogs, evidence has been provided
that epinephrine may play a minor role in liver
glucose output late during exercise [38] probably owing to an increased gluconeogenic precursor level. Furthermore, adrenalectomized
individuals maintain a normal rise in hepatic
glucose production during exercise [39], and
only when epinephrine is infused in these
patients, hepatic glucose production was augmented during the early stages of exercise
(unpublished observation).
Direct stimulation of liver nerves caused an
increase in hepatic glycogenolysis, and the
hypothesis has been put forward that liver nerves
are important for the exercise-induced rise in
liver glucose output. In contrast to this, surgical
or chemical denervation of the liver in various
species did not reduce the exercise-induced increment in hepatic glucose production [32, 33, 40,
41], which indicates that sympathetic liver nerves
are not essential during exercise. In humans, the
role of liver nerves and epinephrine has been
156
studied with application of local anesthesia
around the sympathetic celiac ganglion innervating the liver, pancreas, and adrenal medulla [42].
Pancreatic hormones were standardized by infusion of somatostatin, glucagon, and insulin.
During blockade, the exercise-induced epinephrine response was inhibited by up to 90%, and
presumably liver nerves were also blocked, but
this did not diminish the glucose production
response to exercise. This indicates that sympathoadrenergic activity is not responsible for an
exercise-induced rise in splanchnic glucose output. In further support of this hypothesis, the
exercise-induced increase in liver glucose production was identical in liver-transplanted
patients compared to healthy control subjects as
well as in kidney-transplanted patients who
received a similar hormonal and immunosuppressive drug treatment as liver-transplanted
patients [43]. Liver-transplanted patients were
investigated approx. 8 months after surgery, and
no sign of reinnervation occurred in any of the
patients as judged by the content of norepinephrine in liver biopsies [44]. Finally, in recent
experiments in exercising dogs that underwent a
selective blockade of hepatic α- and β-receptors,
it was demonstrated that circulating norepinephrine and epinephrine do not participate in the
stimulation of glucose production during intense
exercise [45, 46]. Taken together, sympathetic
liver nerves or circulating norepinephrine play no
role in glucose mobilization from the liver during
exercise, and circulating epinephrine only plays a
minor role during intense exercise and late during
prolonged exercise.
drenergic Effect on Skeletal
A
Muscle Carbohydrate Metabolism
Muscle contractions per se increase glucose
uptake, and humoral factors can modify this [47].
Insulin and contractions have a synergistic effect
on glucose uptake with contractions [48], whereas
epinephrine has been demonstrated to decrease
glucose clearance in running dogs [49]. In addition to this, femoral arterial infusion of epinephrine into an exercising leg in humans caused a
M. Kjær and K. Lange
reduction in the normal exercise-induced glucose
uptake [50]. More recently, it has been shown
that in adrenalectomized individuals performing
leg cycling for 45 min at 50% VO2 max followed
by 15 min at 85% VO2 max, the rise in glucose
uptake during exercise was reduced when epinephrine was infused to substitute plasma epinephrine levels normally observed during
exercise (unpublished observation). The mechanism behind this is at present unknown but could
be related to an enhanced glycogenolysis,
increased intramuscular glucose concentration,
or altered uptake of FFA, all changes that can
influence glucose uptake.
It has been shown that adrenergic activity
can enhance the glycogen breakdown in muscle
during contraction both in exercising animals
[51] and in humans [50, 52]. However, those
studies often used supraphysiological doses of
epinephrine, and later studies in humans using
lower doses have only been able to demonstrate
a higher activation of phosphorylase, but could
not demonstrate any marked increase in glycogen breakdown [53]. Noradrenergic activity
probably does not play any role in muscle glycogenolysis, since unilateral hind limb sympathectomy did not diminish glycogen breakdown
in swimming rats [54].
Sympathoadrenergic Activity
and Fat Metabolism
Lipolysis in fat tissue is enhanced by β-adrenergic
activity, and catecholamine responsiveness of
β-adrenergic receptors in adipose tissue is
increased after acute exercise [55]. By the use of
microdialysis of subcutaneous abdominal tissue,
it was demonstrated that nonselective
β-adrenoceptor blockade inhibited the exercise-­
induced increase in dialysate levels of glycerol
[56]. Although this indicates a role for adrenergic
activity in fat metabolism during exercise, the
relative role between sympathetic nerve activity
and circulating norepinephrine/epinephrine is
currently not known. Intravenous infusion of epinephrine in resting humans caused an increase in
lipolytic activity as determined by microdialysis
9
Adrenergic Regulation of Energy Metabolism
of subcutaneous adipose tissue, an effect that was
desensitized by repeated epinephrine infusions
[57]. The direct role of sympathetic nerve activity
on adipose tissue has recently been addressed
using microdialysis, and it was found that during
handgrip exercise, the increase in umbilical glycerol release was attenuated in spinal cord-injured
individuals with impaired sympathetic nerve
activity when compared with healthy control
individuals [58]. It should be noted that this very
moderate type of stress was not able to document
any increase in lipolysis in the clavicular region.
Furthermore, in a recent study, glycerol output in
subcutaneous abdominal adipose tissue was
found to be lower during prolonged arm-­cranking
in spinal cord-injured individuals compared with
controls performing a similar relative workload
(unpublished observation). Taken together, indices are provided that sympathetic nerves to adipose tissue stimulate lipolysis directly during
exercise. If regional differences (visceral vs. subcutaneous fat) exist in responsiveness of the adipose tissue toward increased sympathetic activity,
this could play an important role in the treatment
of adipositas.
Not only adipose tissue but also intramuscular
fat can be stimulated by catecholamines, and both
lipoprotein lipase (LPL) and hormone-­
sensitive
lipase (HSL) play important roles in this regulation [59]. HSL might be under control by both
contractions and epinephrine, and it has recently
been shown that activation of HSL and glycogen
phosphorylase occurs in parallel in adrenalectomized individuals who receive infusion with epinephrine
during
exercise
(unpublished
observation). This could indicate that mobilization
of intramuscular triglyceride and glycogen occurs
simultaneously, stimulated by adrenergic activity,
and that choice of substrate for energy production
takes place at another level.
Summary
Physical exercise causes an increase in adrenergic
activity that can be determined both by changes in
plasma catecholamines and in intraneural sympathetic activity. Release of norepinephrine from
157
contracting muscles and release of epinephrine
from the adrenal medulla are major contributors
to high levels of plasma catecholamines. Both
feed-forward stimulation from motor centers in
the brain and afferent impulses from working
muscles stimulate sympathoadrenergic activity,
and a coupling to oxidative demands of the working muscle is likely. Long-­term physical training
increases the size and secretory capacity of the
adrenal medulla, which may improve exercise
capacity. Sympathoadrenergic activity only plays
a minor role in regulation of hepatic glucose
release, but via depressing insulin secretion and
influencing target tissue, adrenergic activity
improves glycogen and fatty acid mobilization.
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Sex Differences in Energy
Balance and Weight Control
10
Kristin S. Ondrak
I ntroduction: What Is Energy Balance
and What Factors Influence It?
Before understanding how men and women differ with regard to the storage and utilization of
energy, it is important to define the concept of
energy balance. Historically, physiologists
described energy balance as the difference
between the amount of kcal ingested through
food vs. the amount of kcal expended through
physical activity and basal metabolic processes.
The resulting value is one’s body mass. With this
balance in mind, when caloric intake is similar to
caloric expenditure, a state of neutral energy balance occurs and body mass remains stable.
However, when intake exceeds expenditure, positive energy balance ensues and the body stores
the excess energy, thereby increasing body mass.
The opposite results when expenditure exceeds
intake, and this is termed negative energy balance
or energy deficit [38]. While these relationships
are well supported in research, it is also important to note that a variety of factors impact this
relationship, and one cannot simply compare
caloric deficits or excesses over the short term
and expect body mass to change accordingly
[25]. Some of these factors include hormones,
age, acute bouts of exercise, chronic exercise
K. S. Ondrak (*)
Department of Exercise & Sport Science,
University of North Carolina, Chapel Hill, NC, USA
e-mail: kondrak@unc.edu
training, and changes in body composition,
namely, gains or losses in lean mass. These factors will be discussed throughout this chapter, as
well as how they differ between men and women.
In addition to recognizing that energy balance
is more complex than it may appear, it is important to keep in mind that intake and expenditure
should be compared over the long term. When
even small deficits or excesses in daily energy
balance occur day after day, substantial changes
in body mass can result. For example, in a 4-year
cohort analysis study of women, researchers
found that the addition of daily sugar-sweetened
beverages to one’s diet resulted in substantial
increases in body mass and increased their risk
for type II diabetes [41]. These researchers found
that by increasing the consumption of sugar-­
sweetened beverages from less than one per week
to one or more per day, these women consumed
an extra 358 kcal/day and gained ∼4.5 kg on
average [41]. Thus, seemingly small additions to
one’s daily diet can quickly add up to substantial
changes in body mass and energy balance. Along
the same lines, small changes in daily habits may
result in large increases in calories expended. For
example, standing still, as in an elevator, is associated with a caloric expenditure of 1.3 METS,
while taking the stairs expends 4.0–8.8 METS
depending on the speed [15].
Another component to discuss is the expenditure of calories and how that impacts energy balance. When individuals are compared, there is a
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_10
161
K. S. Ondrak
162
substantial amount of variation in the number of
calories burned in a given day. This daily energy
expenditure (EE) is comprised of three main
components: resting metabolic rate (RMR) which
comprises 60–75% of the total calories expended,
diet-induced thermogenesis which accounts for
10–15% of the total, and activity thermogenesis,
which is subdivided into exercise and non-­
exercise components [17]. The largest component, RMR, is closely related to the amount of
fat-free mass (i.e., lean mass) an individual has,
and it is generally higher in men compared to
women [37]. That is, men tend to burn more calories even at rest compared to women, and this is
largely attributed to their higher amounts of metabolically active lean mass. Another complicating factor is age; research has shown that basal
metabolic rate decreases as we get older [24]. For
example, BMR was 4.6% lower in older participants, compared to younger, in a study of individuals ranging from 15 to 64 years of age [28].
Much of what we know about age-related
declines in BMR stems from cross-sectional
studies, though, with most of the difference being
attributed to declines in lean mass. Additional
longitudinal research on age-related declines in
BMR is necessary [24].
In addition to its role in elevating RMR, lean
body mass is also related to diet-induced thermogenesis. That is, greater amounts of lean mass are
associated with a greater number of calories
being burned following consumption of food.
Other factors that influence diet-induced thermogenesis include age, sex, fitness level, and menstrual cycle phase. Interestingly, some studies
have shown that body composition and physical
activity levels were more closely related to EE
than were age and sex [28]. In fact, fat-free mass
had the strongest relationship with 24-h EE, and
the values were similar between women and men
(r2 = 0.79 for females and 0.76 for males) [28].
As might be expected, there is wide variation in
the number of kilocalories an individual burns
each day via physical activity. Daily physical
activity levels and related caloric expenditure
from activity thermogenesis generally decline
with age in both men and women [17]. Research
on sex differences in physical activity levels is
mixed, however; some researchers have reported
lower levels of physical activity EE in women
compared to men [37], while others have reported
no difference [17]. Similarly, sex differences in
measures of EE disappear after taking body composition into account (EE per kg fat-free mass).
In summary, these sex differences in RMR, diet-­
induced thermogenesis, and activity thermogenesis begin to explain how men and women differ
with regard to overall energy balance and weight
control.
After reviewing the components of daily EE
and related energy balance, one can see that there
are many factors involved in energy balance and
the propensity to change or maintain body mass.
This chapter will examine the relationship
between these variables with an emphasis on the
roles of hormones in weight control and how they
differ in males and females. It is important to
note that this chapter focuses on healthy, normal-­
weight adults as the norm, as these processes differ in adults who are overweight or obese as well
as in children.
ormones That Impact Energy
H
Balance, Distribution of Fat,
and Weight Control
Numerous hormones influence EE and body
mass in humans. Some of the same hormones
influence the distribution of body fat, and not surprisingly, the patterns of storage differ between
women and men. For simplicity in this chapter,
the hormones are grouped according to their primary functions as follows: metabolic (leptin,
insulin, ghrelin, anorexigens, and orexigens), sex
(estrogen and androgens), and stress (catecholamines and cortisol) hormones. Their roles and
impact on body mass and weight control are
explained in each respective subsection.
Metabolic Hormones
Several hormones with metabolic functions
impact energy balance in humans, namely, leptin,
insulin, and ghrelin. Leptin, the most recently
discovered hormone, is catabolic in nature and
provides satiety signals to the brain [16, 19, 42,
10 Sex Differences in Energy Balance and Weight Control
50]. It is released by adipose tissue, and its circulating levels are closely related to the amount of
fat mass in adults. Leptin is released in greater
quantities from subcutaneous fat stores compared
to visceral locations [13]. Some researchers suggest that leptin is more closely related to total
body fat levels in females compared to males
[51]. It follows that these authors reported that
females are more sensitive to the actions of leptin
than are males. Leptin plays an important role in
regulating long-term energy balance rather than
the acute fluctuations that occur after each meal
[21]. Once released, leptin, along with insulin,
acts at the level of the hypothalamus where it
induces feelings of fullness, signaling for the person to stop eating. However, leptin’s role in
energy balance is complex as it is influenced by
numerous other hormones including thyroid hormones (T4 and T3), cortisol, insulin, and growth
hormone (GH) [35].
Insulin is another metabolic hormone that
influences energy balance. It is secreted from
pancreatic β-cells in response to increases in
blood glucose. Insulin levels are indicative of visceral fat levels in humans [8, 12]. The correlation
between body fat and insulin is particularly
strong in males, and some authors suggest that
men are more sensitive to insulin than females
[51]. Thus, these sex-related differences in insulin and leptin sensitivity provide a possible mechanism explaining the metabolic differences in
weight control among men and women.
Similar to leptin, insulin reduces appetite
over the long term [16, 19, 21]. As a result, these
hormones are often classified as anorexigenic
(i.e., appetite suppressants). Ironically, individuals with excess body mass (i.e., overweight or
obese) often display resistance to leptin and/or
insulin [16, 19, 33]. This suggests that being in a
state of chronic positive energy balance alters
the body’s ability to respond to satiety cues and
regulate blood glucose levels. These changes
also explain why overweight and obese men and
women are at an increased risk for developing
impaired glucose tolerance and subsequently
type II diabetes.
Ghrelin is another metabolic hormone impacting energy balance. It stimulates hunger in the
short term and, not surprisingly, is released in
163
great amounts by the stomach [21, 29, 30, 53].
Ghrelin levels fall after meals in a manner proportional to the energy load of the meal consumed,
suggesting that this hormone plays a role in inducing satiety and regulating energy balance [21, 29].
Interestingly, ghrelin’s actions are opposite of
insulin, although ghrelin plays a role in its release
[21]. Insulin and ghrelin are negatively correlated;
individuals with high insulin levels tend to have
low ghrelin levels. It is not surprising that this hormonal profile of elevated insulin and low ghrelin
is common in overweight and obese individuals in
particular, as ghrelin levels and body mass index
(BMI) are inversely correlated [21, 34].
Ghrelin’s regulation of acute energy balance
in the short term is due to its effect on the hypothalamus as it stimulates the release of numerous signals that increase hunger. These orexigens
(appetite stimulants) include neuropeptide
Y (NPY), agouti-related protein (AgRP), and
melanocyte-­stimulating hormone (α-MSH) [21,
29]. In one of the first studies of ghrelin during
exercise, plasma acylated ghrelin levels and related
ratings of hunger declined during and following an
acute running bout in young men [9]. This highlights ghrelin’s role in stimulating appetite and is
intuitive that ghrelin levels are suppressed during
exercise. Notably, in a well-designed study of
male and female twin pairs, resting plasma ghrelin
levels were significantly higher in women compared to men [34]. Taken together, these sex differences in anorexigens and orexigens suggest that
the signals controlling hunger and satiety differ
among men and women. Additional anorexigens
including cholecystokinin (CCK), glucagon-like
peptide-1 (GLP-1), and peptide YY (PYY) are discussed in the next subsection along with the influence of sex hormones on each. These differences
are another important consideration for understanding sex-related differences in energy balance
and weight control.
ex Hormones, Orexigens,
S
and Anorexigens
Estrogens and androgens play a large role in body
weight regulation, fat distribution, and energy balance in humans and rodent models. Of these sex
K. S. Ondrak
164
hormones, women tend to have higher levels of
circulating estrogen (technically ­
estrogens –
estradiol-β17, estrone, and estriol), while men
display greater levels of androgens. Estrogen is
related to decreased levels of visceral fat in men
and women; alternatively, androgens are related
to lower levels of visceral fat in males but higher
levels of visceral fat in females [3, 5, 8].
In addition to estrogen’s role guiding the
development of secondary sex characteristics and
bone mass, estrogen also has important metabolic
roles including the reduction of appetite and body
mass [1]. Additionally, estrogen interacts with
the metabolic hormones leptin and insulin to
influence body fat distribution and overall energy
balance.
The release of estrogen impacts appetite by
also decreasing the action and/or effectiveness of
several orexigens (i.e., appetite stimulants)
including ghrelin, neuropeptide Y (NPY), and
melanin-concentrating hormone (MCH) [36, 47].
This data supports estrogen’s role in decreasing
food intake through its influence on orexigens.
Estrogen also leads to a reduction in food intake
through its effects on anorexigenic hormones
including insulin, leptin, serotonin, and cholecystokinin (CCK) [11, 14]. It is important to recognize the importance of other appetite suppressants
Fig. 10.1 Theoretical
model of estrogen’s
relationship with fat,
leptin, and insulin
such as cholecystokinin (CCK), glucagon-like
peptide-1 (GLP-1), and peptide YY (PYY) [44].
Along with leptin, insulin, and ghrelin, these factors have been shown to decrease hunger signals
at hypothalamus [44].
Hormonal Interactions
Researchers have developed a potential model to
explain the relationship between estrogen, fat
distribution, and leptin and insulin [43], as
shown in Fig. 10.1. They theorize that in premenopausal women, estrogen reduces visceral
fat through enhanced lipolysis and decreased
lipogenesis. Estrogen also retains subcutaneous
fat and is related to increases in resting leptin
and reductions in resting insulin levels. However,
in men and postmenopausal women, these
researchers propose that the lower levels of
estrogen and lowered activity of estrogen receptor alpha are related to increases in visceral fat
and reductions in subcutaneous fat and leptin,
while concomitantly insulin levels are increased
[31, 43]. Some of this may be explained by the
direct relationship between leptin and subcutaneous fat as the latter secretes leptin. These sexrelated differences in hormone levels and fat
distribution have been supported by other
researchers as well [10].
Normal Estrogen Levels (As in Premenopausal Women)
↓ Visceral fat
(↑ lipolysis, ↓ lipogenesis)
retains subcutaneous fat
↑ leptin, ↓ insulin
Lower Estrogen Levels (As in Postmenopausal Women and Men)
↑ visceral fat
↓ subcutaneous fat
↓ leptin, ↑ insulin
10 Sex Differences in Energy Balance and Weight Control
Androgens such as testosterone and dehydroepiandrosterone (DHEA; and its sulfated form,
DHEA-S) also play an important role in energy
balance, specifically in influencing where males
and females store their body fat. Women tend to
deposit and retain more adipose tissue around
their hips, buttocks, and thighs, known as a
“gynoid” or “pear” body shape. On the other
hand, men tend to store more fat around their
waist and midsection, known as an “android” or
“apple” body shape [5]. The underlying cause of
the gynoid shape in women and android shape in
men may be due to differences in adipogenesis
and the environment (e.g., hormonal milieu)
within developing adipose cells. For example,
research has shown that women have greater levels of early-differentiated adipocytes compared to
men (measured in abdominal and femoral fat
depots) [45]. These authors also speculated that
sex differences in regional fat distribution may be
due to differences in the microenvironment of the
cells and related apoptosis, innervation, blood
supply, and responsiveness to hormones [45].
In addition to the aforementioned sex differences in body fat distribution, men tend to have
higher levels of visceral fat, while women generally store more fat subcutaneously. Androgen levels may play a role in these relationships as greater
amounts of visceral fat have been associated with
lower androgen levels in men and excess androgen levels in women [5]. Unfortunately for men,
visceral fat carries an increased cardiovascular
disease risk compared to subcutaneous fat. This
often puts men at an increased risk for cardiovascular disease [3–5]. Not surprisingly, inverse correlations have been reported between body fat and
EE from physical activity in men (r = −0.34,
p < 0.03) [37]. Therefore, sex differences in
estrogen and androgens are related to body fat and
its distribution; these differences in turn influence
EE and balance in men and women.
Stress Hormones
Stress hormones such as catecholamines and cortisol are another group of hormones that have a
large impact on energy balance. To further com-
165
plicate the matter, stress hormones also interact
with sex hormones, thus altering their actions
[32]. Catecholamines such as epinephrine and
norepinephrine are released in response to sympathetic nervous system stimulation when a
stressor occurs, whether real or perceived; a common example is exercise. In response to catecholamine release, appetite centers in the
hypothalamus are suppressed, and related food
intake declines.
The primary function of catecholamines and
the stress hormone cortisol is to provide energy
for the body to face the stressor. Rather than stimulating appetite, these hormones cause the body
to break down stored energy, and one example is
by stimulating lipolysis. This process is also
enhanced by thyroid hormones, cortisol, growth
hormone, and estrogen [35]. Thus, there are
numerous hormonal signals triggering fat breakdown throughout the body. These hormones and
their related lipolytic actions are extremely
important during exercise, especially at low to
moderate intensities. Catecholamines also
increase available energy by increasing glycogenolysis in both the liver and the muscle [54]. The
data concerning sex differences in catecholamines at rest and during exercise is conflicting;
some studies have shown no difference in men
and women, while others have reported slightly
higher levels of epinephrine and norepinephrine
in men [54]. Likewise, research has shown that
men and women have similar levels of both blood
and salivary cortisol measures at rest [27].
However, these authors identified sex differences
in salivary cortisol in response to stress, such that
women in the luteal phase of their menstrual
cycle had similar responses to men and both were
greater than women in the follicular phase of
their menstrual cycle or women on oral contraceptives [27]. This suggests that both sex and the
menstrual cycle phase of women should be considered when evaluating cortisol levels and their
impact on energy balance.
While the functions of numerous metabolic,
sex, and stress hormones that impact energy balance were discussed, the following sections will
describe how these hormones are affected by
physical activity. The related changes in appetite,
166
energy intake, and energy balance will also be
discussed, and sex-related differences in these
relationships will be discussed when possible.
ow Does Physical Activity
H
Influence Appetite, Satiety,
and Energy Balance?
It is commonly believed that increased level of
physical activity and exercise leads to stimulation of appetite. However, research in this area
has reported mixed results. For example,
researchers have shown that in general, physical
activity does not have a large influence on the
balance between intake and expenditure [7].
That is, increases in physical activity do not necessarily stimulate appetite, just as reductions in
physical activity do not lead to substantial
decreases in appetite. Blundell [6] has built upon
the work of previous researchers and proposed
two zones to describe how changes in physical
activity relate to changes in appetite and food
intake, a regulated zone and a non-regulated
zone. In the regulated zone, increases in physical
activity are related to increased drive to eat;
however in the non-­regulated zone, reductions in
physical activity, or becoming sedentary, are not
indicative of reductions in food intake. Thus,
lack of regulation shows that caloric expenditure
is not always related to hunger signals. This
author also suggested that increasing one’s level
of physical activity should help move them into
the regulated zone where these variables are
more tightly connected, hence regulated. These
trends between physical activity level and energy
intake were supported in a recent review of
cross-sectional research [2]. These authors
reported that low levels of habitual physical
activity were associated with higher levels of
energy intake compared to those with medium
and even high levels of physical activity; however, individuals reporting very high levels of
physical activity had the highest level of energy
intake as one would expect [2]. Hormonal
changes also exist in relation to low energy
intake. For example, ghrelin, cortisol, and NPY
have been shown to increase, while leptin and
K. S. Ondrak
PYY, among others, decrease in women experiencing chronic negative energy balance [20].
The relationship between an acute bout of
exercise and appetite was summarized recently in
a comprehensive review by Dorling et al. [18].
Following acute bouts of aerobic exercise, studies have shown a slight suppression of appetite,
especially when the bout was ≥60% of VO2 peak,
and no consistent sex differences have been
shown [18]. This suppression is likely related to
reductions in acylated ghrelin which is reduced
following exercise of this intensity [18]. These
alterations do not last long, though, with hormonal levels and related appetite returning to
normal levels within hours of the cessation of
exercise. The effect of chronic exercise training
on appetite and food intake is not as clear, as
studies have shown increases, no change, and
even reductions in appetite [18].
The next question, then, is whether sex differences exist in the relationship between physical
activity and appetite. The literature in this area is
mixed. In a recent review article, Thackray et al.
[46] concluded that there was little to no evidence
showing sex differences in the relationship
between these variables. However, other researchers have reported that women exhibit a greater
tendency to either increase energy intake following physical activity or have a more difficult time
achieving negative caloric balance and weight
loss via physical activity, compared to men [7].
This conclusion has been supported by other
researchers as well [23, 48] and by the greater
prevalence of obesity in women worldwide compared to men (15% of women vs. 11% of men)
[52]. Similar results were reported in a review of
290 participants from 22 studies as physical activity was inversely related to percent body fat in
males (partial r = 0.35, p < 0.001) but not in
females (partial r = 0.16, p > 0.05), after accounting for age [48]. While the mechanisms behind
these differences were beyond the scope of the
reviews, authors have hypothesized that sex differences in fat may be attributable to women’s
need for sufficient fat stores for successful reproduction [7, 23].
In another study of exercise and appetite, a
group of 12 normal-weight men and women
10 Sex Differences in Energy Balance and Weight Control
exercised for 14 days, and the resulting changes
in energy balance were examined [49].
Participants took part in periods of no additional
exercise as well as moderate- and high-intensity
exercise, with the order counterbalanced, and
were fed ad libitum. The authors reported that the
additional EE from the exercise did not elicit
equal increases in energy intake; rather the average caloric compensation was only ∼30%. This
yielded average negative energy balances ranging
from −0.9 to −3.8 MJ/day in women and −1.6
to −4.7 MJ/day in men [49]. The authors
acknowledge that while tightly controlled, this
study only represents the initial compensation to
exercise-­induced energy deficits and longer studies are needed to elucidate the chronic relationships between these variables. Such studies as
these provide additional data that contributes to
our understanding of sex-related differences in
weight control and long-term energy balance.
However, much more work in this area of research
is necessary.
167
resting leptin and insulin and increases in acylated ghrelin in response to exercise performed in
a state of negative energy balance, and women
had higher acylated ghrelin and lower insulin following the bout, compared to men [23]. This supports the notion that following physical activity,
women’s appetite is stimulated to a greater degree
than men’s [23]. These researchers proposed a
model to help explain some trends they observed.
Specifically, they proposed that in men, physical
activity reduces appetite but does not change
metabolic hormones such as ghrelin, insulin, and
leptin substantially. Therefore, there would be no
compensatory changes in energy intake for men,
and the energy deficit caused by the increased
expenditure would result in reduced body fat.
Conversely, in women, physical activity may
have no effect on appetite yet cause large hormonal changes. These changes, along with the
maintenance of appetite in women, may result in
a state of positive energy balance which may preserve or even increase their levels of body fat
[23]. This model may explain why women tend
to maintain or even gain body mass or fat in
Sex Differences in Exercise-Induced
response to physical activity, whereas men typically do not. As previously described, the comHormonal Changes
mon theory explaining these sex differences is
Energy expenditure from physical activity is that the hormonal differences exist to protect
influenced by the metabolic-, stress-, and sex-­ women’s fat mass to a greater extent than men’s
related hormones described earlier in this chap- in order to ensure successful reproduction.
ter. In turn, hormone release is altered in response However, not all studies have supported these sex
to physical activity and exercise. Acute bouts of differences in the hormones regulating appetite
exercise are related to increases in catechol- or their response to exercise [46]. Nonetheless,
amines, growth hormone, cortisol, thyroid hor- the theoretical model of Hagobian and Braun is
mones, estrogen, and androgens, while insulin an interesting hypothesis that future research
and leptin tend to decrease [35]. These patterns of needs to examine more closely.
hormonal release differ somewhat in response to
Researchers have also examined sex differchronic exercise training, as many are decreased ences in substrate utilization during exercise. In a
in response, but some remain unchanged.
study of seven men and seven women endurance-­
To further complicate these relationships, trained cyclists matched by peak oxygen uptake
some authors have found that hormonal changes (VO2 peak) per kg lean body mass, there were no
in response to exercise may differ between men sex differences in respiratory exchange ratio
and women. For example, GH levels have been (RER) during moderate-intensity exercise,
shown to increase to a greater degree in women, ­indicating similar contributions from fat and carcompared to men, during exercise [39]. bohydrates [40]. Likewise, there were no sex difAdditionally, in a study examining the hormonal ferences in insulin, epinephrine, or norepinephrine
changes following exercise performed in several concentrations during exercise. However, the
energy states, researchers noted reductions in sources of fat differed between the sexes as men
K. S. Ondrak
168
derived less energy from myocellular triacylglycerols compared to females, and males also had a
larger greater proportion of energy that was unaccounted for in fat and carbohydrates sources.
Other researchers have reported conflicting
results regarding sex differences in fuel metabolism during cycling. Some researchers found that
women rely more heavily on fats during exercise
(51% vs. 44% for women and men, respectively),
while men obtain more energy from carbohydrates (53% and 46%, respectively) when cycling
for 2 hours at 40% of their maximal oxygen
uptake (VO2 max) [26]. Furthermore, these exercise responses are affected in women by the
phase of the menstrual cycle and associated
estrogen hormonal changes [22]. These differences are likely attributable to the higher concentrations of epinephrine and norepinephrine seen
in men compared to women. It is important to
recognize that while conflicting results are often
reported, readers must consider the intensity and
duration of the exercise within studies as they
have a large influence on substrate use and the
related hormone response. In summary, collectively these studies provide additional data supporting sex-related differences in energy usage,
energy balance, and ultimately weight control.
Summary
This chapter examined the influence of several
hormones and their effect on energy balance and
weight control in men and women. Sex differences were explored and include the following:
females generally store more fat subcutaneously,
while men store more fat in visceral locations;
females are more sensitive to the actions of leptin,
while men are more sensitive to insulin; and each
of these hormones is closely related to one’s level
of adiposity. These sex differences often place
men at an increased risk for the development of
cardiovascular disease due to its association with
visceral fat. In addition, the hormonal profile of
women favors conservation of fat mass, most
likely for reproduction, and some data show that
women respond differently to physical activity
compared to men. These differences suggest that
sex-specific strategies may be necessary for
maintaining or altering energy balance and body
mass in men and women.
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Exercise Training in the Normal
Female: Effects of Low Energy
Availability on Reproductive
Function
11
Anne B. Loucks
Abbreviations
ACSM
BMI
BW
EA
EI
FFM
GH
GnRH
HPG
IGFBP
IGF-I
kcal
LBM
LH
NEB
NEEE
PYY
RM
T3
TEEE
WEE
American College of Sports Medicine
Body mass index
Body weight
Energy availability
Energy intake
Fat-free mass
Growth hormone
Gonadotropin-releasing hormone
Hypothalamic-pituitary-gonadal
IGF-binding protein
Insulin-like growth factor-I
Kilocalories
Lean body mass
Luteinizing hormone
Negative energy balance
Non-exercise energy expenditure
Peptide YY
Resting metabolism
Tri-iodothyronine
Total energy expended during exercise
Waking energy expenditure
A. B. Loucks (*)
Biological Sciences, Ohio Musculoskeletal and
Neurological Institute, Ohio University,
Athens, OH, USA
e-mail: loucks@ohio.edu
Introduction: The Female Athlete
Triad
This chapter summarizes the studies in our laboratory and others that identified low energy
availability as the key factor causing the Female
Athlete Triad and identifies four distinct origins of
low energy availability among female athletes. In
2007, the American College of Sports Medicine
(ACSM) published a revised position stand on the
Female Athlete Triad [1], which replaced its earlier position stand on the same subject [2]. The
revised position stand corrected the former misunderstanding of the Triad as a narrow syndrome
consisting of disordered eating, amenorrhea,
and osteoporosis by describing the Triad more
broadly as the harmful effects of low energy availability on menstrual function and bone mineral
density. The revised position stand emphasized
that energy availability can be severely reduced
by exercise energy expenditure alone without
clinical eating disorders, disordered eating, or
even dietary restriction. It also explained that low
energy availability induces more menstrual disorders than amenorrhea and that these functional
hypothalamic menstrual disorders must be carefully distinguished by differential diagnosis from
other kinds of menstrual disorders not caused by
low energy availability that are, therefore, unrelated to the Triad. The revised position stand also
explained that bone mineral density in young
athletes must be quantified in terms of Z-scores
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_11
171
172
instead of T-scores and that during adolescence
low energy availability can cause Z-scores to
decline as T-scores increase. Subsequently, treatment and return to play guidelines for the Triad
were published in 2014 by the Female Athlete
Triad Coalition [3, 4]. In 2014, an International
Olympic Committee consensus statement introduced the term Relative Energy Deficiency in
Sport to extend the concept of the Female Athlete
Triad to include effects of energy deficiency
beyond the reproductive and skeletal systems in
men as well as women [5]. This chapter focuses
on effects of low energy availability on reproductive function, specifically in women.
Hypothetical Mechanisms
of Functional Hypothalamic
Menstrual Disorders in Exercising
Women
As in other fields of research, competing schools
of thought developed to explain the high prevalence of menstrual disorders observed in exercising women. Of the several early mechanisms
proposed, three were most widely held.
Body Composition
In 1974, body composition was offered as an
explanation for the amenorrhea observed in
anorexia nervosa patients [6]. This idea was a
refinement of an earlier hypothesis about body
weight accounting for the timing of menarche
[7]. The body composition hypothesis held that
menarche occurs in girls when the amount of
energy stored in their bodies as fat rises to a critical 17% of their body weight, and that menstrual
function is lost later when their body fat declines
to less than a critical 22% of body weight [6].
The body composition hypothesis was the
most widely publicized explanation for menstrual disorders in athletes in the lay community
and the most widely embraced by the clinical
community, even though it was the least widely
accepted within the scientific community. The
hypothesis was based entirely on correlations
without any supporting experimental evidence
A. B. Loucks
[8]. Actually, observations of athletes did not
consistently verify an association of menstrual
status with body composition (e.g., Ref. [9]) and
did not display the correct temporal relationship
between changes in body composition and menstrual function (for reviews, see [10–13]). Rather,
eumenorrheic and amenorrheic athletes were
found to span a common range of body composition [14] leaner than that of eumenorrheic
sedentary women. In addition, after the growth
and sexual development of prepubertal animals
had been blocked by dietary restriction, normal
luteinizing hormone (LH) pulsatility resumed
only a few hours after ad libitum feeding was
permitted, before any change in body weight or
composition could occur [15]. Moreover, when
surgical reduction of the stomachs of severely
obese women (body weight ~130 kg; body mass
index [BMI] ~47) reduced the amount of food
that they could eat, rapid weight loss and amenorrhea occurred while the patients were still obese
(body weight ~97 kg; BMI ~35) [16].
Despite such criticisms, scientific interest in
the body composition hypothesis was renewed
with the discovery in 1994 of the adipocyte hormone leptin [17], with the observation of statistically significant correlations between leptin
levels and body fatness in rodents and humans
(e.g., Ref. [18]) and with the discovery of leptin
receptors on hypothalamic neurons. Since then,
an abundance of experimental evidence from
rodents and human has demonstrated that a minimal level of leptin is permissive (i.e., necessary
but not sufficient) for sexual development and
function [19]. This permissive effect occurs indirectly via receptors on hypothalamic kisspeptin
neurons that communicate with the hypothalamic
gonadotropin-releasing hormone (GnRH) neurons that regulate LH pulsatility [20].
A 9-month double-blind, randomized, clinical
trial administered pharmacological doses of leptin
to women with functional hypothalamic amenorrhea whose BMI was in the range 18–25 kg/
m2 [21]. Prior to treatment, their leptin levels
(mean ± SD = 4.6 ± 2.0 ng/ml) were within the
lower portion of the range (7.4 ± 3.7 ng/ml) cited
by the leptin assay manufacturer (Millipore Corp.)
for women in this range of BMI [22]. Leptin levels
comparable to those reported by the manufacturer
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
have been found in other women with similar ranges
of BMI [23–29]. The leptin dosages administered
to the women with functional hypothalamic amenorrhea in this experiment raised their leptin levels
more than tenfold (mean ± SD = 59 ± 37 ng/ml).
Yet menstrual cycles occurred only intermittently,
with the number of menstruating women fluctuating from month to month between 3 of 10 (30%)
and 4 of 7 (57%).
By contrast, nutritional counseling has
restored spontaneous menstrual cycles in 75%
of women with functional hypothalamic amenorrhea within 5 months [30]. Although leptin was
originally thought to communicate information
about fat stores, it was later found to vary profoundly in response to fasting, dietary restriction,
refeeding after dietary restriction, and overfeeding before any changes in adiposity occurred
[31–34]. This led to the hypothesis that leptin
also signals information about dietary intake
and specifically carbohydrate intake after leptin
synthesis was found to be regulated by the tiny
flux of glucose through the hexosamine biosynthesis pathway in both muscle and adipose
tissue [35]. In eumenorrheic and amenorrheic
athletes, leptin was found to differ not in its average concentration, but rather in the presence and
absence, respectively, of a diurnal rhythm [23],
and the diurnal rhythm was found to depend not
on energy intake but rather on energy availability
or more specifically on carbohydrate availability
[27]. Thus, if leptin does participate in the functional regulation of the GnRH pulse generator in
exercising women, it seems more likely to do so
as a signal of low energy or carbohydrate availability than as a signal of low energy stores.
Energy Availability
In 1980, Warren was the first to suggest that
menstrual function in dancers might be disrupted
by an “energy drain” [36], but an empirically
testable energy availability hypothesis was first
clearly stated in terms of brain energy availability by Winterer, Cutler, and Loriaux in 1984 [37].
They hypothesized that failure to provide sufficient metabolic fuels to meet the energy requirements of the brain causes an alteration in brain
173
function that disrupts the GnRH pulse generator,
although the mechanism of this alteration was
unknown.
At the organismal level, the energy availability hypothesis recognizes that mammals partition
energy among several major metabolic activities,
including cellular maintenance, immunity, thermoregulation, locomotion, growth, and reproduction [38] and that the expenditure of energy
in one of these functions, such as locomotion,
makes it unavailable for others, such as reproduction. Considerable observational data from
biological field trials supports this idea and indicated that the dependence of reproductive function on energy availability operates principally in
females (For reviews, see [38–42]. Experiments
had induced anestrus in Syrian hamsters by
food restriction, by the administration of pharmacological blockers of carbohydrate and fat
metabolism, by insulin administration (which
shunts metabolic fuels into storage), and by cold
exposure (which consumes metabolic fuels in
thermogenesis) [38]. Disruptions of reproductive function were independent of body size and
composition.
The energy availability hypothesis was also
supported by endocrine observations of athletes.
Amenorrheic athletes displayed low blood glucose levels during the feeding phase of the day
[43], low insulin and high IGF binding protein-1
(IGFBP) during the fasting phase [43], loss of the
leptin diurnal rhythm [23], high fasting acylated
ghrelin [44], high peptide YY (PYY) [45], and
low tri-iodothyronine (T3) levels in the morning
[46, 47]. All of these abnormalities in metabolic
substrates and hormones are signs of energy deficiency. T3 regulates basal metabolic rate, and low
T3 occurs in numerous conditions, from fasting
to cancer, in which dietary energy intake is insufficient to meet metabolic demands. In addition,
eumenorrheic and amenorrheic athletes both displayed low insulin and high IGFBP-1 levels during the feeding phase of the day, as well as low
leptin [23] and elevated growth hormone (GH)
levels over 24 hours [43]. Indeed, eumenorrheic
and amenorrheic athletes were found to be distinguished not by different 24-hour mean concentrations of leptin but rather by different amplitudes
in the diurnal rhythm of leptin [23].
174
Amenorrheic and eumenorrheic athletes
reported similar stable body weights, despite
dietary energy intakes similar to those of sedentary women [46, 48–52]. That is, they reported
their dietary energy intakes to be much less than
would be expected for an athlete’s level of physical activity. This apparent discrepancy between
stable body weight and unexpectedly low dietary
energy intake was controversial. Since energy
intake and expenditure are very difficult to measure accurately, the apparent discrepancy might
have been attributable to methodological errors.
Some investigators attributed the apparent discrepancy between energy intake and expenditure
in athletic women to underreporting of dietary
intake [53, 54], because such underreporting is
common in all populations [55], but underreporting did not account for the abnormalities in
metabolic substrates and hormones observed in
athletes. Furthermore, behavior modification and
endocrine-mediated alterations of resting metabolic rate operate to stabilize body weight despite
dietary energy excess and deficiency [56].
Exercise Stress
The exercise stress hypothesis held that exercise
disrupts the GnRH pulse generator by activating the hypothalamic–pituitary–adrenal axis. In
order for the stress hypothesis to be meaningfully
independent of the energy availability hypothesis, however, the adrenal axis must be activated
independently of the energy cost of the exercise.
Certainly, there are central and peripheral
mechanisms by which the adrenal axis can disrupt the ovarian axis [57], and prolonged aerobic exercise without glucose supplementation
does activate the adrenal axis. Selye first induced
anestrus and ovarian atrophy in rats by abruptly
forcing them to run strenuously for prolonged
periods [58]. Later, others also induced anestrus
by forced swimming [59, 60], by forced running
[61], and by requiring animals to run farther and
farther for smaller and smaller food rewards [62,
63]. The elevated cortisol levels induced in such
experiments were interpreted as signs of stress,
and the resulting disruptions of the hypothalamic-­
A. B. Loucks
pituitary-­gonadal (HPG) axis were widely interpreted as evidence that “exercise stress” has a
counter-regulatory influence on the female reproductive system.
Amenorrheic athletes also display mildly
elevated cortisol levels [43, 48, 64–66]. This
observation was the basis for attributing their
amenorrhea to stress. Mild hypercortisolism is
also associated with amenorrhea in patients with
functional hypothalamic amenorrhea [67] and
anorexia nervosa [68]. This interpretation overlooked the glucoregulatory functions of cortisol,
which inhibit skeletal muscle glucose uptake and
promote skeletal muscle proteolysis for hepatic
gluconeogenesis in response to low blood glucose levels [69]. Thus, it was possible that the
mild hypercortisolism observed in amenorrheic
athletes might have reflected a chronic energy
deficiency rather than exercise stress.
At the time, it was not known whether the
adrenal cortical axis mechanisms that disrupt
the HPG axis in forced exercise experiments on
animals also operate in voluntarily exercising
women. Indeed, up to that time, all animal experiments investigating the influence of the “activity
stress paradigm” on reproductive function had
confounded the stress of exercise with the stress
of the method used to force animals to exercise.
These experiments had also been confounded by
the energy cost of the exercise performed, and
glucose supplementation during exercise was
found to blunt the usual rise in cortisol in both
rats [70] and men [71]. As a result, in 1990 the
literature on stress contained only ambiguous
evidence that the stress of exercise disrupts the
HPG axis in either animals or humans.
Prospective Clinical Experiments
xperiments Confounding Exercise
E
Stress and Energy Availability
Several investigators attempted to induce menstrual disorders through chronic exercise training, but most [72–75] applied only a moderate
volume of exercise, or the volume of exercise
was increased gradually over several months, and
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
diet was uncontrolled or unquantified. One study
[75] selected physically trained subjects who
appeared to have been luteally suppressed before
the study even began [76].
Only one experiment had successfully induced
menstrual disorders in regularly menstruating
women [77]. Modeled on Selye’s early animal
experiments [58], this single successful experiment imposed a high volume of aerobic exercise
abruptly, thereby suppressing follicular development, the LH surge, and luteal function in a large
proportion of the subjects in the first month and
in an even larger proportion in the second. Both
proportions were greater in a subgroup fed a controlled weight loss diet than in another subgroup
fed for weight maintenance, but even the weight
maintenance subgroup may have been underfed, since behavior modification and endocrine-­
mediated alterations of resting metabolic rate
operate to stabilize body weight despite dietary
energy excess and deficiency [56].
Such experiments, in which outcome variables are properties of the menstrual cycle,
require sustained observations over a period of
several weeks. Such prolonged experimental protocols suffer from practical problems with subject retention and compliance with experimental
treatments. To avoid these difficulties, shortterm experimental protocols were developed in
which LH pulsatility was chosen as the outcome
variable, because ovarian function is critically
dependent on LH pulsatility. Of course, shortterm effects on LH pulsatility are not proof of
chronic effects on ovarian function, but hypotheses about mechanisms regulating LH pulsatility
could be tested in highly controlled short-term
experiments, and then chronic effects could be
confirmed in prolonged experiments later.
One such short-term experimental protocol
found that a combination of increased exercise
and dietary restriction disrupts LH pulsatility
during the early follicular phase [78]. LH pulse
frequency during 12 waking hours was lower in
four habitually physically active women when
their exercise training regimen was increased
during a few days of dietary restriction than
during dietary supplementation. However, this
experiment did not determine whether LH pulse
175
frequency could be suppressed by exercise without dietary restriction or whether the stress of
exercise had a suppressive effect on LH pulsatility beyond the impact of the energy cost of exercise on energy availability.
Experiments Distinguishing
the Independent Effects of Exercise
Stress and Energy Availability
For several years, we focused our efforts on a
series of studies that we called the “Excalibur”
experiments that were designed to determine the
independent effects of exercise stress and energy
availability on the HPG axis [28, 29, 79–83]. For
these experiments, we defined energy availability operationally as dietary energy intake minus
exercise energy expenditure. Conceptually, this
corresponds to the amount of dietary energy
remaining after exercise training for all other
physiological functions. Although not the actual
physiological quantity hypothetically affecting
the HPG axis at the cellular level, our operational
definition in behavioral terms had the advantage
of being readily measurable and controllable.
We controlled the dietary energy intake of our
subjects by feeding them diets of known amount
and composition as their only food during the
experiments. We also required them to exercise
under supervision in our laboratory on a treadmill while we measured and controlled their
energy expenditure until they had expended a
predetermined amount of energy. In the absence
of any empirically operational definition of stress
[84], we defined exercise stress independently as
everything associated with exercise except its
energy cost.
Through careful subject selection, we took
steps to minimize the influence of potentially
confounding factors. Healthy, regularly menstruating, habitually sedentary, nonobese, non-­
smoking women 18–34 years of age at least
5 years past menarche, with no recent history
of dieting, weight loss, or aerobic training were
recruited. Before being admitted to the study,
these volunteers underwent an extensive screening procedure, including written medical, men-
A. B. Loucks
176
strual, dietary, and athletic histories, a physical
examination, a 12-lead resting electrocardiogram,
a 7-day prospective dietary record, determination
of body composition by hydrostatic weighing or
whole body air-displacement plethysmography,
and a treadmill test to determine their aerobic
capacity. Volunteers were admitted into experiments only if they presented no current use of
medications including oral contraceptives and no
history of heart, liver, or renal disease, diabetes,
and menstrual or thyroid disorders. They must
also have had documented prospective records of
menstrual cycles 26–32 days in length for at least
the previous 3 months. They were required to be
18–30% body fat, with habitual energy intakes
between 35 and 55 kcal/kg lean body mass
(LBM)/day based on their 7-day diet records,
with maximal aerobic capacities less than 42 ml
O2/kg body weight (BW)/min, and they must
have been performing less than 60 minutes of
habitual aerobic activity per week for the previous 3 months.
The narrow range of our subjects’ menstrual
cycle lengths implied that we restricted our subject pool to the central 60% of menstrual cycle
lengths in the population and that from this pool
we chose women whose menstrual cycle lengths
were in the least variable 20% of the population
[85]. Thus, if anything, our subjects’ reproductive systems were robust against disturbance by
commonly occurring environmental and behavioral influences. We could be confident, therefore,
that if our treatments disrupted the reproductive
systems of these women, they would disrupt the
reproductive systems of other women, too. We
could also be confident that our subjects’ metabolism had not been disturbed by any confounding
medical conditions or dietary or exercise habits
before our treatments were applied.
Excalibur I
Excalibur I [79] was designed to investigate
whether exercise stress had any suppressive effect
on T3 levels independent of the impact of the
energy cost of exercise on energy availability. We
were interested in T3 because it regulates the rate
of energy expenditure at rest and because it was
known to be suppressed in amenorrheic athletes.
We reasoned that if the energy cost of exercise
necessitates such major metabolic adjustments
as the suppression of reproductive function, then
these metabolic adjustments might be mediated
in part by suppressing T3.
Over the course of the Excalibur experiments,
our insight into how to correctly quantify energy
availability (EA) for subjects of various body
sizes gradually matured. At the time of Excalibur
I, we normalized energy intake (EI) and exercise
energy expenditure to body weight (BW). We
also measured exercise energy expenditure as the
total energy expended during exercise (TEEE), as
measured by an ergometer.
EA = ( EI − TEEE ) / BW
In Excalibur I, we found that severely low
energy availability (8 kilocalories per kilogram
of body weight per day, kcal/kgBW/day) suppressed T3 levels by 15%, while exercise stress
had no effect on T3. T3 levels were suppressed
similarly regardless of whether energy availability was reduced by dietary energy restriction or
by exercise energy expenditure. Furthermore,
the suppression of T3 in exercising women was
prevented by supplementing their diet in compensation for the energy cost of their exercise.
These findings were consistent with the energy
availability hypothesis and inconsistent with the
exercise stress hypothesis.
Excalibur II
Excalibur II [80] was designed to reveal whether
T3 levels in exercising women vary in linear proportion to energy availability or are suppressed
abruptly at a particular threshold of energy
­availability. By this time we had realized that
very little energy expenditure occurs in body fat.
Accordingly, we changed our normalization of
energy intake and expenditure to lean body mass
(LBM) which would exclude body fat.
EA = ( EI − TEEE ) / LBM
We administered various levels of energy availability to exercising women and found that the suppression of T3 by low energy availability occurred
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
abruptly at a threshold of energy availability near
25 kcal/kgLBM/day. For our women of average
body size (59 kg) and composition (24.5% body
fat), that threshold was about 1000 kcal/day.
Excalibur III
Normal ovarian function depends not on some
stable concentration of LH but rather on the
occurrence of pulsatile surges of LH concentrations in the blood at regular intervals. These
pulses correspond to regular secretory bursts
of LH from the pituitary gland in response
to similar secretory bursts of GnRH from the
hypothalamus. The frequency (at intervals of
70–180 minutes) and amplitude of these pulses
vary around the menstrual cycle. In sedentary
women in the early follicular phase, the pulsatile
pattern is characterized as high frequency and
low amplitude. In regularly menstruating athletes, the pulses occur less often and are larger in
amplitude but still at regular intervals. In amenorrheic athletes, LH pulses occur even less often
and irregularly [48].
Therefore, in Excalibur III [81, 82], we investigated whether exercise has any suppressive
effect on LH pulsatility beyond the impact of its
energy cost on energy availability. The design
of Excalibur III is illustrated in Fig. 11.1. For
4 days in the mid-follicular phase of two menstrual cycles, we controlled the energy availability of two groups of women. During one cycle,
we administered a balanced energy availability
of 45 kcal/kgLBM/day, and during the other
cycle, we administered a low energy availability
of 10 kcal/kgLBM/day. One group of subjects
performed no exercise during the two treatment
periods. A second group performed the same
large volume of high-intensity exercise that we
had utilized in Excalibur I (30 kcal/kgLBM/day
at 70% VO2max; maximal aerobic capacity]).
We imposed balanced and low energy availabilities on the non-exercising group by feeding
them 45 and 10 kcal/kgLBM/day, respectively.
We imposed the same balanced and low energy
availabilities on the group performing 30 kcal/
kgLBM/day of exercise by feeding them 75 and
40 kcal/kgLBM/day, respectively.
Between Excalibur II and III, we had had
another insight into the proper quantification of
energy availability. Prior to Excalibur III [81, 82],
90
90
45
45
B
0
kcal . kg–1 FFM
Fig. 11.1 Experimental
design of Excalibur
III. Dietary energy
intake (I) and exercise
energy expenditure (E)
were controlled to
achieve balanced
(B = 45 kcal/kgLBM/
day) and deprived
(D = 10 kcal/kgLBM/
day) energy availability
(A = I-E) treatments.
Deprived energy
availability was achieved
by dietary restriction
alone in sedentary
women (S) and by
exercise energy
expenditure alone in
exercising women (X)
(1 kcal = 4.18 kJ).
(Reproduced with
permission from [82])
177
0
-45
I
E
I
A
E
A
-45
90
90
45
45
D
0
0
-45
-45
S
X
A. B. Loucks
178
we had calculated energy availability by subtracting
total energy expenditure during exercise (TEEE)
from dietary energy intake. While we were designing Excalibur III, however, we recognized that if
our exercising subjects had not been exercising,
their other routine activities during the same hours
would have resulted in some non-­exercise energy
expenditure (NEEE). Therefore, the actual energy
expenditure due to exercise itself (EEE) was less
than the total energy expenditure measured during
exercise (EEE = TEEE – NEEE). This adjustment
would be especially important for Excalibur III, in
which some subjects exercised and others did not.
So, in Excalibur III and our later experiments, we
changed again the way we calculated energy availability by subtracting from dietary energy intake
only the portion of total energy expenditure during
exercise that was directly attributable to the exercise itself.
during exercise that was specifically attributable to the exercise. In retrospect, our subjects’
energy expenditure in routine activities on a non-­
exercising day during the same 3 hours when
they exercised in Excalibur II had amounted
to 5 kcal/kgLBM/day, and our calculations of
energy availability had been underestimated by
the same amount.
At the end of each of the 4-day treatments
in Excalibur III, we admitted the women to a
general clinical research center and drew blood
samples from them at 10-minute intervals for
24 hours. Later, we measured the amount of
LH in each sample and used a special statistical
computer program to detect and to calculate the
frequency and amplitude of their LH pulses. We
determined the effects of energy availability on
these frequencies and amplitudes by contrasting
data taken while performing the same exercise at
different energy availabilities, and we determined
the independent effect of exercise stress by conEA = ( EI − EEE ) / LBM
trasting groups exercising differently at the same
We achieved this by using an activity monitor energy availabilities.
to measure our subjects’ energy expenditure in
We found that low energy availability reduced
their normal daily activities during the same LH pulse frequency and increased LH pulse
hours of the day when they would be exercising amplitude, while exercise stress had no suppresin our experiment. We then subtracted this non-­ sive effect on LH pulsatility beyond the impact of
exercise energy expenditure in routine activities the energy cost of exercise on energy availabilfrom their total energy expenditure during exer- ity (Fig. 11.2). LH pulsatility was disrupted by
cise to obtain the amount of energy expenditure extreme energy restriction alone and by extreme
0
20
-1
15
Pulses . day–1
Fig. 11.2 Effects of
low energy availability
on LH pulsatility in
Excalibur III. Left:
Luteinizing hormone
(LH) pulse frequency in
sedentary (S) and
exercising (X) women
with the same balanced
energy availability
(45 kcal/kgLBM/day).
Right: Reduction in LH
pulse frequency caused
by low energy
availability (10 kcal/
kgLBM/day) in
sedentary (S) and
exercising (X) women.
∗
p < 0.01. (Adapted
from [81, 82])
-2
*
-3
10
-4
-5
5
-6
0
S
X
-7
*
*
S
X
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
exercise energy expenditure alone. Dietary supplementation prevented the suppression of LH
pulsatility by exercise energy expenditure. Others
have shown that short-term fasting also reduces
LH pulse frequency in sedentary women during
the early follicular phase [86, 87] and that in lean
women, ovarian function is also impaired during
the ensuing menstrual cycle [87].
In Excalibur III, low energy availability also
suppressed plasma glucose, insulin, insulin-like
growth factor-I (IGF-I), leptin, and T3 while raising growth hormone (GH) and cortisol levels.
All these effects are reminiscent of abnormalities observed in amenorrheic athletes [43, 46–48,
64–66].
This contradiction of the exercise stress
hypothesis has been confirmed by more prolonged experiments on animals. Amenorrhea was
induced in monkeys by training them to run voluntarily on a motorized treadmill for longer and
longer periods, while their food intake remained
constant [88]. Then their menstrual cycles were
restored by supplementing their diets without any
moderation of their exercise regimen [89]. The
exercise stress hypothesis was also contradicted
in a novel animal model of the entire Female
Athlete Triad [90]. In this modified activity
stress paradigm, rats were habituated to voluntary wheel running for 90 days and then randomized to control and restricted diets for the next
90 days. Although both groups ran similar distances and expended similar amounts of energy
in exercise, estradiol was suppressed, estrous
cycling ceased, ovaries were atrophied, and the
bone mineral content of the femur and tibia were
reduced only in the underfed rats.
The suppression of LH pulse frequency by
low energy availability in Excalibur III was actually smaller in exercising women than in non-­
exercising women with the same low energy
availability [82]. This result was unexpected, and
it suggested that LH pulsatility might actually
depend on a more specific metabolic factor that
is easily confused with energy availability, but
which is less compromised by exercise energy
expenditure than by dietary energy restriction.
Research in other mammals suggests that
GnRH neuron activity and LH pulsatility are
179
actually regulated by brain glucose availability
[38, 41]. The adult female human brain oxidizes
about 80 g of glucose each day at a continuous
rate. This must be provided daily by dietary carbohydrate, because the brain’s rate of energy
expenditure can deplete liver glycogen stores in
less than a day [91]. To that end, moderate exercise oxidizes as much glucose in an hour.
In the non-exercising women in Excalibur
III, low energy availability due to dietary energy
restriction reduced carbohydrate intake by 77%.
This reduction in carbohydrate intake was similar to the 73% increase in carbohydrate oxidation revealed by respiratory gas analysis in the
exercising women during the balanced energy
availability treatment. By contrast, carbohydrate
oxidation increased only 49% in the exercising
women under low energy availability conditions.
This alteration in fuel selection conserved almost
70% of the brain’s daily glucose requirement.
Thus, exercise may compromise brain glucose
availability less than dietary energy restriction,
and this may account for the smaller disruption
of LH pulsatility that we observed in exercising
women than in dietary-restricted women. Thus,
LH pulsatility may depend specifically on carbohydrate availability rather than energy availability in women, just as it does in other mammals.
Excalibur IV
Excalibur IV [83] was designed to reveal whether
refeeding reverses the suppression of LH pulsatility in women as quickly as it does in other
mammalian species. In food-restricted female
rats [15, 92] and ewes [93], and in fasted heifers [94] and male rhesus monkeys [95], a single
ad libitum meal stimulates LH pulses within
2 hours. Such observations have been interpreted
to imply that the physiological signals produced
by a single large meal are sufficient to activate
the hypothalamic GnRH neurons that control LH
pulsatility [96].
We suspected that the restoration of LH pulsatility by refeeding might be considerably slower
in energetically disrupted women than in other
mammals, because the human brain requires so
much more energy than does the brain of any
other mammal. The brain competes against all
180
other tissues of the body for energy, and the adult
human brain requires 20% of basal metabolic
energy, compared to only 2% for most species
and 8% for nonhuman primates [97]. Therefore,
we suspected that a single meal might not provide enough energy to activate GnRH neurons in
energetically disrupted women.
To stringently test this hypothesis, we assayed
LH in blood samples drawn from women at
10 minute intervals for 48 hours during the mid-­
follicular phase, first during 24 hours on the fifth
day of low energy availability treatments and
then during 24 hours of aggressive refeeding. A
combination of moderate dietary energy restriction (25 kcal/kgLBM/day) and moderate exercise
energy expenditure (15 kcal/kgLBM/day) was
administered to impose a low energy availability
of 10 kcal/kgLBM/day. The aggressive refeeding
regimen was comprised of 15 meals providing a
total of 85 kcal/kgLBM/day. Combined with the
same exercise treatment, the energy availability
during the 24 hours of aggressive refeeding was
70 kcal/kgLBM/day.
Compared to measurements of LH pulsatility in 18 other women studied previously in our
laboratory under balanced energy availability
conditions and at the same phase of the menstrual cycle, low energy availability suppressed
LH pulsatility unambiguously in five of the eight
subjects treated in this experiment. Their LH
pulse frequency was reduced 57% to 8.2 ± 1.5
pulses/24 hours, well below the 5th percentile of
LH pulse frequencies in energy balanced women
(14.6 pulses/24 hours), while their LH pulse
amplitude was increased 94% to 3.1 ± 0.3 IU/L,
well above the 95th percentile of LH pulse amplitudes in energy balanced women (2.5 IU/L).
Amongst these women, aggressive refeeding raised LH pulse frequency by only
2.4 ± 1.0 pulses/24 hours, still far below the 5th
percentile of LH pulse frequency in energy balanced women. Meanwhile, the unambiguously
elevated LH pulse amplitude was completely
unaffected (Δ = 0.0 ± 0.4 IU/L) by aggressive
refeeding. Results were similar when all eight
subjects were included in the analysis. Aggressive
refeeding pushed the group as a whole to, but not
past, the 5th and 95th percentiles of LH pulse
A. B. Loucks
frequency and amplitude, respectively. Thus, as
we had suspected, 24 hours of a refeeding protocol much more aggressive than the ad libitum
refeeding protocols commonly employed in animal experiments had very little restorative effect
on LH pulsatility in our energetically suppressed
women.
Excalibur V
In an experimental protocol similar to that of
Excalibur II, Excalibur V determined the dose-­
response effects of low energy availability on
LH pulsatility in habitually sedentary, regularly
menstruating young women [28]. To do this,
we administered balanced and one of three low
energy availabilities (45 and either 10, 20, or
30 kcal/kgLBM/day) to healthy, habitually sedentary, regularly menstruating women for 5 days.
The design is illustrated in Fig. 11.3.
We found that LH pulsatility was disrupted
within 5 days below a threshold of energy availability at ~30 kcal/kgLBM/day (Fig. 11.4). This
was, in fact, the same actual energy availability
that we had reported as 25 kcal/kgLBM/day in
Excalibur II [80], because we had underestimated energy availability by 5 kcal/kgLBM/day
in Excalibur II, as described in the discussion of
Excalibur III above.
The disruption of LH pulsatility below
30 kcal/kgLBM/day in Excalibur V was consistent with many observational studies of amenorrheic runners, all of which indicated energy
availabilities less than 30 kcal/kgLBM/day [98].
It was also consistent with the only prospective
study of the refeeding of amenorrheic athletes, in
which menstrual cycles had been restored in runners by increasing their energy availability from
25 to 31 kcal/kgLBM/day [99]. Energy availabilities below 30 kcal/kgLBM/day have also been
reported in eumenorrheic athletes [98], 80% of
whom display subclinical ovarian disorders in
which the suppression of progesterone may also
impair fertility [100].
In the same experiment, we also determined
the dose-response effects of low energy availability on several metabolic substrates and
hormones. Down to an energy availability of
30 kcal/kgLBM/day, the responses of insulin,
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
I)
60
Energy Intake and Expenditure
(kcal/kgLBM/day)
181
50
d
olle
tar
Die
y
erg
n
yE
(
ake
Int
ntr
Co
40
30
20
10
0
Controlled Exercise Energy Expenditure (X)
0
5
10
15
20
25
30
35
40
45
50
Energy Availability (kcal/kgLBM/day)
Fig. 11.3 Experimental design of Excalibur V. Women
were assigned to contrasting energy availability treatments of 45 and 10, 45 and 20, and 45 and 30 kcal/
kgLBM/day. All subjects performed a controlled exercise energy expenditure of 15 kcal/kgLBM/day in aero-
75
Percent (%)
50
A/3
25
0
-25
F
-50
-75
0
10
20
30
40
50
Energy Availability (kcal/kgLBM/day)
Fig. 11.4 Incremental effects of energy availability on
LH pulse amplitude (A/3) and LH pulse frequency (F) in
Excalibur V. Effects are expressed relative to values at
45 kcal/kgLBM/day. Effects on LH pulse amplitude have
been divided by three for graphical symmetry. As energy
availability declines from energy balance at approximately 45 kcal/kgLBM/day, effects begin at a threshold at
approximately 30 kcal/kgLBM/day and become more
extreme as energy availability is further reduced below
20 kcal/kgLBM/day. (Reproduced with permission from
[28], Copyright 2003, The Endocrine Society)
cortisol, insulin-like growth factor (IGF)-I/IGFbinding protein (IGFBP)-1, IGF-I/IGFBP-3,
leptin, and T3 maintained plasma glucose lev-
bic exercise at 70% VO2 max under supervision, while
their dietary energy intake was controlled to achieve the
intended energy availabilities. (Reproduced with permission from [28], Copyright 2003, The Endocrine
Society)
els to within 3% of normal values. Below that
threshold, however, plasma glucose levels fell
despite further increases in the responses of the
metabolic hormones, and effects on LH pulsatility appeared.
Excalibur V also revealed the dose-response
effects of low energy availability on biochemical markers of bone turnover [101]. Urinary concentrations of N-telopeptide of type I collagen,
a marker of the rate of whole body bone resorption, rose as estradiol concentrations declined,
when energy availability was lowered to 10 ­kcal/
kgLBM/d. By comparison, markers of bone formation declined at higher energy availabilities.
Concentrations of serum carboxy-terminal propeptide of type I procollagen, a marker of bone
type I collagen synthesis, and insulin declined
linearly with energy availability. By contrast,
concentrations of osteocalcin, a marker of bone
mineralization, declined abruptly below 30 kcal/
kgLBM/day together with IGF-I and T3, which
modulates the hepatic synthesis of IGF-I in
response to GH stimulation. Such uncoupling
of bone turnover, with increased resorption and
reduced formation, can lead to irreversible reductions in bone mineral density [102].
182
Excalibur VI
The prevalence of amenorrhea has been reported
to decline from 67% in marathon runners younger
than 15 years of gynecological age to only 9%
in those who were older [103]. Meanwhile, in
the general population, the incidence of menstrual disorders declines during the decade after
menarche as fertility increases [104]. Excalibur
VI investigated whether these two observations
might both be explained by a declining sensitivity of LH pulsatility to low energy availability as the energy cost of growth decreases [29].
Calcium balance, which is an index of growth,
does not decline to zero until 14 years of gynecological age [105].
In Excalibur VI, contrasting balanced and low
energy availabilities (45 and 10 kcal/kgFFM/day)
were administered to healthy, habitually sedentary,
regularly menstruating, older adolescent women
(5–8 years of gynecological age, ~20 years of calendar age) and young adult women (14–18 years
of gynecological age, ~29 years of calendar age)
for 5 days. Low energy availability suppressed
LH pulsatility in the adolescents but not in the
adults, even though metabolic and endocrine signals of energy deficiency (i.e., plasma glucose,
β-hydroxybutyrate, insulin, cortisol, T3, leptin,
IGF-1, and GH) were altered as much or more in
the adults as in the adolescents [29].
This insensitivity of LH pulsatility to energy
deficiency in adult women was subsequently confirmed by a corresponding insensitivity of ovarian function to energy deficiency [106]. In that
experiment, the energy availability of women
25–40 years of age was reduced to ~25 kcal/
kgFFM/day for 4 months by a combination of
dietary restriction (~600 kcal/day) and exercise
(~200 kcal/day). This subthreshold energy deficiency reduced the body fatness of these reproductively mature women from 32% to 27% but caused
no more than a mild suppression of luteal function.
An adult reproductive system that is more
robust against insults of energy deficiency may
be explained by a greater availability of glucose
to the brain in adults than in adolescents at the
same energy availabilities. This might occur if
peripheral tissues in full-grown adults do not
compete as aggressively against the brain for
A. B. Loucks
available energy or carbohydrate. Alternatively,
the sensitivity of sensors in the central nervous
system to signals of energy deficiency may
decline during adolescence. These possibilities
remain to be investigated.
ther Efforts to Manipulate Energy
O
Availability in Habitually Sedentary
Women
A recent study by Lieberman et al. [107] investigated the effects of energy availability on menstrual function by reanalyzing data collected
in an earlier experiment that had attempted to
administer controlled negative energy balance
(NEB) treatments of −15%, −30%, and −60% to
separate groups of habitually sedentary regularly
menstruating women for 3 months [108]. Thirty-­
five women with 5–15 years of gynecological
age and ovulatory cycles as long as 35 days were
studied, even though cycles of 36 days were to
be classified as a clinical menstrual disturbance
(oligomenorrhea) and the average within-person
annual standard deviation of cycle length at the
subjects’ age is 4 days [85].
In practice, NEB turned out to be less negative and more widely dispersed than intended
(mean ± 2SD, −8 ± 10%, −22 ± 21%, and
−42 ± 9%). Moreover, metabolic hormone
indicators of energy deficiency did not display
dose-­
response effects of group differences in
NEB. Assuming the underlying diet and exercise
data were correct, Lieberman et al. calculated
energy availability values in each menstrual cycle
and found a continuum of energy availability
treatments from 18 to 51 kcal/kgFFM/day.
Unfortunately, Lieberman et al. did not report
the effects on metabolic hormones. They found
no dose-response effects of energy availability
on ovarian steroids. Altogether, they found that
36% of 105 menstrual cycles across the range of
energy availability displayed menstrual disturbances and 85% of these were subclinical (luteal
phase deficiency and anovulation). Collectively,
only one menstrual cycle was missed.
Lieberman et al. concluded that their results
“do not support that a threshold energy availability exists below which menstrual disturbances
are induced,” thereby appearing to confirm the
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
Female Athlete Triad as a continuum of interrelated disorders. However, given the 10–15%
incidence of oligomenorrhea and the 15–65%
incidence of subclinical menstrual disturbances
in free-living women of the same gynecological
age [109, 110], the observations of Lieberman
et al. are better interpreted as what would be
expected without any intervention. Moreover,
without a crossover design and without dose-­
response effects of energy availability on any
physiological indicator of energy deficiency,
Lieberman et al. simply lack evidence that the
disturbances they observed were caused by the
treatments administered.
Reversal of Amenorrhea
in Amenorrheic Athletes
Cialdella-Kam et al. [111] administered a
carbohydrate-­
protein dietary supplement of
360 kcal/day to athletes with clinical menstrual
disorders (7 amenorrheic and 1 oligomenorrheic).
After 6 months, the eight athletes had resumed
menses with seven of them resuming ovulation.
However, it should be noted that the investigators
calculated EA without subtracting non-exercise
energy expenditure NEEE. Therefore, as they
acknowledged in another paper [112], their pre
and post EA values probably underestimated
actual EA values by 1–2 kcal/kgFFM/day. Prior
to this study, there had been pilot studies published of amenorrheic athletes who increased
caloric intake for several months, and changes in
menstrual status were observed [99, 113].
Pre and post EA values depended, of course,
on the definition of exercise. When exercise was
defined as activity when energy expenditure was
greater than 4.0 METS, the dietary supplement
increased energy availability from 37 to 45 kcal/
kgFFM/day (p = 0.10). However, when exercise
was defined more broadly to include all planned
exercise plus bicycle commuting and all walking,
energy availabilities were lower with the dietary
supplement increasing them from 28 when amenorrheic to 39 kcal/kgFFM/day after restoration of
menses (p = 0.09) [112].
More prospective research is needed to determine successful behavioral strategies that amenorrheic athletes with low energy availability can
183
use to resume menstrual status. For example,
research on appetite suppression by exercise and
dietary restriction suggests that it may be important for athletes to consume planned amounts of
energy at planned times, by discipline instead of
appetite [114].
onclusions About the Hypothetical
C
Mechanisms of Functional
Hypothalamic Amenorrhea
in Female Athletes
We are unaware of any experiments that have
determined the independent effect of body composition on the HPG axis. From the available
experimental data, however, it would appear
to be more likely that a lean body composition
and disruption of the HPG axis are both effects
of low energy availability than that a lean body
composition disrupts the HPG axis. Our shortterm experiments on women have demonstrated
that exercise stress has no suppressive effect on
LH pulsatility beyond the impact of the energy
cost of the exercise on energy availability. These
short-term 4–5-day experiments investigating the independent effects of exercise stress
and low energy availability on LH pulsatility
predicted and, as we expected, were later confirmed by long-term experiments investigating
the ­independent effects of exercise stress and
low energy availability on estrus and menstrual
cycles. Prospective controlled experiments on
both humans and animal models have demonstrated that the factor disrupting the HPG axis
in physically active women is low energy availability. These experiments suggest that women
may be able to prevent or to reverse menstrual
disorders by dietary reform alone without moderating their exercise regimen. As long as dietary
energy intake is managed to keep energy availability above 30 kcal/kgLBM/day, there may be
no need to interfere with endurance, strength,
and skill training. Finally, the susceptibility of
women to the disruption of reproductive function by energy deficiency appears to be substantially greater in those younger than 15 years of
gynecological age.
184
auses of Low Energy Availability
C
in Female Athletes
Effective treatment of low energy availability in
athletes requires that the origin of the low energy
availability be identified. Low energy availability
behaviors appear to derive from four different origins [1, 114]. Some athletes intentionally reduce
energy availability in a rational, but misguided,
pursuit of the body size, body composition, and
mix of metabolic fuel stores that are thought to
optimize performance in their particular sport.
Complex objectives may include reducing fat
mass while increasing muscle mass and maximizing glycogen stores. For such athletes who
reduce energy availability excessively, nutrition
education and guidance regarding appropriate,
individualized intermediate and ultimate goals,
schedules, and methods may be sufficient to
modify their diet and exercise behavior.
In other athletes, low energy availability originates in an eating disorder. Eating disorders are
clinical mental illnesses that are often accompanied by other mental illnesses [115, 116].
Therefore, eating disorders require psychiatric
treatment, often inpatient treatment, as well as
nutritional counseling. Because the mortality
of eating disorders is so high, sports organizations need to develop institutional methods for
distinguishing undernourished athletes with eating disorders from those who do not have eating
disorders. This distinction may not be obvious,
since undernourished athletes who are only trying to optimize performance may practice many
of the same disordered eating behaviors (e.g.,
skipping meals, vomiting, using laxatives, etc.)
as athletes with eating disorders. Athletes with
eating disorders are distinctive in their resistance
to the efforts of coaches, trainers, nutritionists,
and physicians to modify their behavior.
The third origin of low energy availability in
athletes is the suppression of appetite by prolonged exercise. This effect is compounded by
the appetite-suppressing effect of diets containing high percentages of carbohydrates, which are
commonly recommended to athletes in endurance
sports. Even though many studies on this subject
have been published over the past 20 years [114,
A. B. Loucks
117], appetite remains a largely neglected topic
in the field of sports nutrition. Indeed, the word
“appetite” appears only twice, in the recently
revised joint position stand of the American
Dietetic Association, the Dietitians of Canada,
and the American College of Sports Medicine on
nutrition and athletic performance [118].
Briefly, food deprivation increases hunger,
but the same energy deficit produced by exercise
energy expenditure does not [119]. The appetite-­
suppressing effect of prolonged exercise has been
demonstrated in controlled experiments with
protocols ranging from a few hours to 12 weeks
[114]. The effect is mediated by the orexigenic
hormone ghrelin, which induces us to begin
eating, and by several anorexigenic hormones
(including peptide YY, glucagon-like peptide 1,
and pancreatic polypeptide) that induce us to stop
eating. Exercise does not stimulate an increase
in ghrelin concentrations but does stimulate
increases in the concentrations of anorexigenic
hormones (see associated Chaps. 12 and 30). As
a result, “there is no strong biological imperative
to match energy intake to activity-induced energy
expenditure” [120].
Meanwhile, the appetite-suppressing effect of
diets containing high percentages of c­ arbohydrates
has been demonstrated in experimental protocols
ranging from a week [121] to a month [122, 123].
As the percentage of carbohydrates in the diet was
reduced, ad libitum energy intake spontaneously
increased. As a result, the actual amount of carbohydrate consumed was preserved even though the
percentage of carbohydrates in the diet decreased
from 67% to 55%. The mechanism of this effect
has not yet been identified but may involve the
greater bulk and fiber content of carbohydraterich foods.
Importantly, the large effects of these two factors are additive [121] so that together they can
reduce energy availability below 30 kcal/kgFFM/
day in endurance athletes. To avoid inadvertent
low energy availability, therefore, athletes in
endurance sports need to be trained to eat by discipline (i.e., planned amounts of selected foods at
scheduled times) instead of appetite.
The fourth apparent origin of low energy
availability among female athletes is that young
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
women under-eat for social reasons unrelated to
sport. Around the world, about twice as many
young women as young men at every decile of
body mass index perceive themselves to be overweight, and the numbers actively trying to lose
weight are even more disproportionate [124].
Alarmingly, the disproportion even increases as
BMI declines, so that almost 9 times as many
lean women as lean men are actively trying to
lose weight! Indeed, more young female athletes
report improvement of appearance than improvement of performance as a reason for dieting
[125]. As a result, social issues unrelated to sport
may need to be addressed to persuade female athletes to eat by discipline beyond their appetites.
ources of Error in the Estimation
S
and Control of EA
In publications of the Excalibur experiments,
the portion of body composition apart from fat
mass is termed LBM. It is better termed fat-free
mass (FFM). Then, as currently understood,
energy availability (EA) is quantified by measuring dietary energy intake (EI), exercise energy
expenditure (EEE), and fat-free mass (FFM). EA
is then calculated as:
185
EA = ( EI − EEE ) / FFM
A common source of error (by us in Excalibur I
and II and by others) in studies of EA in athletes
has derived from the misunderstanding of EEE
as the total energy expenditure that would be
measured by an ergometer during exercise. This
misunderstanding has led to underestimations of
EA, misinterpretations of data, and unwarranted
criticisms of the concept.
As described in the discussion of Excalibur
III above, EEE is defined as the extra energy
expended beyond the energy that would have been
expended if no exercise had been performed (see
Fig. 11.5). Defining EEE in this way enables EA
to be fairly compared between different groups
of subjects who do and do not exercise and
between repeated observations of the same subjects when they do and do not exercise. Because
energy expenditure varies with routine activities during the day, to calculate EA consistently
with the Excalibur experiments, non-­
exercise
energy expenditure (NEEE) must be measured
on another non-exercising day during the same
waking hours when exercise is performed. Then
EEE is calculated as the difference between total
energy expenditure during exercise (TEEE) and
NEEE on the other day:
EE
EEE
Non-Exercise Waking Activity
Resting Metabolism = 30 kcal/kgFFM/day
00
03
06
09
12
Fig. 11.5 Calculation of exercise energy expenditure
(EEE). (A. Top) EEE is the amount of energy that a
woman expends because she is an athlete and does not
include the energy she expends in resting metabolism and
other waking activities. (B. Middle) Ergometers measure
total energy expenditure during exercise (TEEE), which
overestimates EEE by ~2 kcal/kgFFM/d per hour of exer-
15
18
Hrs
21
24
cise. For high-intensity exercise of short duration, the
resulting error in calculating energy availability as
EA = (EI – TEEE)/FFM is negligibly small for clinical
purposes. (C. Bottom) For low-intensity exercise of long
duration, however, the error in EA = (EI – TEEE)/FFM is
very large and will lead to unwarranted changes in diet
and exercise behavior. (Adapted from [126])
A. B. Loucks
186
EEE = TEEE − NEEE
In an example described in a previous review
[126], the resting metabolism (RM) of an athlete in energy balance on a non-exercising day is
assumed to be 2/3 of her EI. For EI = 2100 kcal/
day (8.8 MJ/day), RM = 1400 kcal/day (5.8 MJ/
day) or 58 kcal/hour (244 kJ/h). If she sleeps
8 hours, her routine activities in waking energy
expenditure (WEE) would expend the rest of her
EI. Ignoring for simplicity other sources of diurnal
variation in energy expenditure, her average rate
of WEE would be 700 kcal/16 hours = 44 kcal/h
(182 kJ/h). If her fat-free mass (FFM) is 45 kg,
then her rate of non-exercise energy expenditure
(NEEE) during exercise would be:
NEEE = ( RM + WEE ) / FFM = ( 58 + 44 ) / 45 =
2.3 kcal / kgFFM / h ( 9.5 kJ / h )
If the athlete’s total energy expenditure during a
40-minute run is TEEE = 500 kcal, then:
EEE = TEEE − NEEE = 500 / 45 − ( 2 / 3) ∗ 2.3 =
11.1 − 1.5 = 9.6 kcal / kgFFM
For such brief, high-intensity exercise, NEEE
(1.5 kcal/kgFFM) is too small to cause an error
in judgment about the adequacy of EA. However,
if the same TEEE had been expended in 4 hours
of gymnastics training, NEEE (9.2 kcal/kgFFM)
would be too large to ignore:
EEE = TEEE − NEEE = 500 / 45 − 4 ∗ 2.3
= 11.1 − 9.2 = 1.9 kcal / kgFFM
If this gymnast were to restrict her dietary intake
to EI = 1575 kcal/day, ignoring NEEE would lead
to excessive concern about her EA and unwarranted demands for behavior modifications:
With NEEE:
EA = ( EI − EEE ) / FFM = 1575 / 45 − 1.9
= 33.1 kcal / kgFFM / day (138 kJ / kgFFM / day )
Ignoring NEEE:
(EA = EI − TEEE ) / FFM = 1575 / 45 − 9.6
= 25.4 kcal / kgFFM / day (106 kJ / kgFFM / day )
Other sources of error in the calculation of
EA derive from errors in the estimation of EI,
EEE, and FFM. As pointed out in another review
[126], a few simple calculations with realistic
values quickly reveal that the greatest efforts
should be made to record EI accurately. Consider
an athlete with body mass = 60 kg, %Fat = 25%,
EEE = 500 kcal/day, and EI = 2100 kcal/day
(8.8 MJ/day). Her FFM is (1–0.25) × 60 = 45 kg
and her EA is
EA = ( EI − EEE ) / FFM = ( 2100 − 500 ) / 45
= 35.6 kcal / kgFFM / day (149 kJ / kgFFM / day )
A 2% error rate in %Fat determinations is not
uncommon with body composition analyzers.
Subsequently, a 2% overestimate of %Fat (i.e., 27%
in the above example) leads to an underestimate of
FFM (43.8 kg) and a negligible error in EA:
EA = ( 2100 − 500 ) / 43.8
= 36.5 kcal / kgFFM / day
(153 kJ / kgFFM / day )
A 10% error in EEE would correspond to a runner erring by half a mile in the length of a 5-mile
run. A 10% underestimation of EEE leads to a
similarly negligible error in EA:
EA = ( 2100 − 450 ) / 45
= 36.7 kcal / kgFFM / day
(153 kJ / kgFFM / day )
Underestimations of EI as big as 20% have been
suspected by some dietitians. A 20% underestimation of EI would lead to a large error in EA:
EA = ( 0.8 × 2100 − 500 ) / 45
= 26.2 kcal / kgFFM / day
(110 kJ / kgFFM / day )
Even a 10% underestimation of EI would lead to
a substantial error in EA:
EA = ( 0.9 × 2100 − 500 ) / 45
= 30.9 kcal / kgFFM / day
(129 kJ / kgFFM / day )
11
Exercise Training in the Normal Female: Effects of Low Energy Availability on Reproductive Function
187
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Ghrelin Responses to Acute
Exercise and Training
12
Jaak Jürimäe
Introduction
The importance of physical exercise to influence
energy balance and body mass is widely recognized [1]. A complex neuroendocrine system is
involved in the regulation of energy homeostasis
including central and peripheral tissues [2, 3].
Important to this regulatory system is the existence of several appetite hormones, including
adipose and gut tissue hormones that communicate the status of body energy stores to the hypothalamus [2]. Energy intake is an integral to
energy balance and is regulated via neuronal circuits interacting with gut hormones, key among
these being ghrelin and peptide YY [4, 5]. It
appears that peptide YY functions as a negative
feedback signal and is responsible for inducing
satiety and cessation of eating after food intake
[5]. In contrast, ghrelin is a hormone well known
for its acute orexigenic properties stimulating
food consumption [6, 7]. Changes in these circulating appetite hormones influence the physiological drive to eat, weight gain and also reproductive
function [4]. Furthermore, ghrelin may also be
involved in pubertal development, where rapid
growth and development need careful coordination of energy balance and appetite regulatory
signals [4]. Finally, circulating ghrelin concentraJ. Jürimäe (*)
Institute of Sport Sciences and Physiotherapy,
University of Tartu, Tartu, Estonia
e-mail: jaak.jurimae@ut.ee
tions may vary dramatically depending on specific body composition, physical activity and
physical fitness parameters [2]. This chapter
focuses on the available information about the
effects of acute exercise and chronic exercise
training on the secretion of ghrelin.
Ghrelin, a peptide secreted by distinct endocrine cells of the stomach, was first described as
an endogenous ligand for the growth hormone
secretagogue receptor [8]. However, ghrelin role
in body mass regulation is more prominent than
its role in growth hormone secretion [9]. Ghrelin
promotes positive energy balance by increasing
appetite and food intake [10, 11]. Specifically,
the rise in circulating ghrelin concentration
before a meal is a physiological signal for hunger
and the body’s cue for meal initiation [12].
Therefore, the rise in ghrelin levels and hunger
occurs independent of food and time of day cues
[12]. Meal responses of ghrelin are related to
acute caloric intake over a typical day of eating in
normal-weight subjects [13]. Furthermore, ghrelin levels have been demonstrated to be negatively correlated with 24-h caloric intake [14],
and ghrelin concentrations decrease after caloric
intake and increase while fasting [2]. The
decrease in ghrelin release is related to the specific amount of calories ingested [15].
Accordingly, ghrelin is responsive to diet- and
exercise-induced changes in body mass [16].
In addition to total ghrelin, acylated and des-­
acylated forms of ghrelin have been described
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_12
193
194
[17]. The acylated form of ghrelin is thought to
be essential for ghrelin biological activity [18],
whereas unacylated ghrelin has been suggested
to be biologically inactive [19]. Specifically,
acylated ghrelin has been reported to be associated with the regulation of growth hormone
secretion, cardiac performance, cell proliferation
and adipogenesis and affects appetite, food intake
and energy balance [8, 20, 21]. There are also
some studies suggesting that unacylated ghrelin
is related to insulin resistance [22–24]. It has also
been demonstrated that total ghrelin and acylated
ghrelin are positively correlated [25–27] and both
forms of the ghrelin potentially play a role in
energy balance [28]. Based on these results, it
could be suggested that acylated and desacylated
forms of ghrelin change similar to changes in
energy balance, and total ghrelin concentration
can be used as a biomarker in energy balance
studies [4, 29, 30]. Future studies, nonetheless,
are needed to better clarify the responses of total
ghrelin and its specific forms in various conditions of energy balance.
hrelin During Growth
G
and Maturation in Children
Ghrelin is a hormone that could influence
somatic growth [4] and sexual maturation [31].
Specifically, a negative association of circulating
ghrelin level with age [4, 31] and pubertal development [32] has been found. It has been hypothesized that ghrelin provides a link between
energy homeostasis, body composition and
pubertal development through actions on the
hypothalamus [33], where ghrelin stimulates the
secretion of gonadotropin-releasing hormone,
which in turn stimulates the secretion of the
gonadotropins required for pubertal onset [16].
It has been found that the initiation of puberty
substantially decreases ghrelin concentrations in
both sexes [4, 31]. A negative correlation
between ghrelin and testosterone has been found
in boys entering puberty [32]. In contrast, a
recent study demonstrated no effect of testosterone and estradiol on ghrelin decrease during
pubertal growth in boys and girls, respectively
J. Jürimäe
[4]. It was found that a drop in circulating total
ghrelin to its lowest levels occurred during peak
pubertal growth [4]. Furthermore, Cheng et al.
[4] suggested that adolescent ghrelin concentrations may be more strongly associated with
markers of somatic growth than sexual maturation. Specifically, circulating ghrelin levels were
inversely correlated with insulin-like growth factor-1 concentrations and with annual height and
weight velocity in both sexes [4]. Accordingly,
the decrease in circulating ghrelin levels at the
onset of puberty is apparent [4, 34, 35], despite
the fact that puberty is characterized by increased
appetite and food intake [31] and ghrelin is
known to stimulate appetite [28, 36]. Research
suggests that there could be an increased sensitivity for appetite stimulation by ghrelin over
puberty [31] and/or low ghrelin concentrations
signal adequate nutritional status to support
rapid somatic growth and development of reproductive capacity [4] to sustain growth in this
period. In addition, elevated energy expenditure
and, therefore, also an increased energy intake in
physically active children during pubertal maturation are linked to higher circulating ghrelin
levels in these children compared with physically inactive children [36]. Accordingly, it could
be argued that regular physical activity still
causes higher ghrelin levels during puberty to
stimulate appetite and food intake to cover
higher energy homeostasis [36]. This is supported by the finding that there is a negative correlation of cardiorespiratory fitness as measured
by peak oxygen consumption with total ghrelin
[37] and acylated and desacylated forms of ghrelin [38] in boys during puberty. However, different forms of ghrelin were not associated with
directly measured physical activity intensities in
pubertal boys with differing body composition
[38]. Collectively, these results demonstrate that
somatic growth and maturation are associated
with ghrelin, which concentrations decrease
with advancing age and puberty. However, further longitudinal studies throughout puberty in
children with various physical activity and body
composition levels are needed to better understand how physical fitness and activity may
influence circulating ghrelin concentrations dur-
12
Ghrelin Responses to Acute Exercise and Training
ing puberty in children with different body
­composition values before any definitive conclusions can be drawn.
In longitudinal investigations with growing
and maturing athletes, total ghrelin levels have
been studied in female gymnasts [35, 39] and
male and female swimmers [40, 41]. It could be
argued that regular sport training increases ghrelin levels to stimulate appetite and food intake to
cover higher energy homeostasis in these young
athletes [2, 42]. Ghrelin may act as a hormone
signalling a need for energy conservation, and
ghrelin secretion is triggered to counter a further
deficit in energy storage to help to maintain body
mass [2, 43]. Accordingly, higher basal ghrelin
concentrations have been found in prepubertal
and adolescent athletes when compared with
untrained controls [34, 35, 44]. However, basal
ghrelin levels decreased in both prepubertal
rhythmic gymnasts and age-matched lean
untrained controls over a 12-month study period
[39], showing that an increasing age decreases
ghrelin concentrations similarly in both groups
despite large differences in daily energy expenditure [2, 36]. Therefore, ghrelin concentrations
were still significantly higher in the rhythmic
gymnasts when compared with untrained controls at both measurement times during prepuberty [39]. However, when rhythmic gymnasts
and untrained controls reached puberty, ghrelin
levels were decreased in both groups and were
not different between groups with different
energy expenditure levels [35]. Similarly, a significant decrease in basal ghrelin levels was
observed in male swimmers after the evolution of
puberty [41], while basal ghrelin levels were not
changed in pubertal female swimmers with
advancing pubertal maturation over a 2-year
study period [40]. It can be suggested that basal
ghrelin levels are higher in prepubertal children
who participate in sport training in comparison
with age-matched untrained controls, while basal
ghrelin levels decrease when young athletes
reach puberty even in the presence of chronically
elevated energy expenditure [2, 36]. Furthermore,
pubertal maturation appears to reduce circulating
ghrelin concentrations in growing athletes of
both sexes, despite heavy athletic activity [2, 36].
195
hrelin Relationships with
G
Adiposity and Energy Availability
Ghrelin levels are significantly lower in obese
individuals [45–47] and substantially elevated in
patients with anorexia nervosa [12, 48, 49], proposed as a likely adaptive mechanism response
[12, 50]. Accordingly with these patterns, there is
a negative association of ghrelin concentration
with body mass [32, 51], body mass index [32,
52], total body fat mass [34, 51], visceral fat mass
[53, 54] and total body lean mass [32, 55]. It has
also been suggested that circulating ghrelin level
could be regarded as a signal of decreased total
body lean mass in healthy elderly females [56].
In addition, there are also studies to show an
inverse correlation between ghrelin concentration and body height [32, 57, 58] and body height
velocity [4] during growth in children.
Diet-induced weight loss in obese individuals
has been accompanied by increases in circulating
total ghrelin concentrations [59]. For example,
plasma ghrelin levels increased by 17% in overweight women who reduced their body mass by
4.5% after 10-week body weight loss intervention programme [60], while a 6-month supervised weight loss programme that caused 17.4%
body weight loss induced 24% increase in ghrelin levels [61]. In addition, short-term diet-­
induced body weight loss in obese subjects
resulted in higher total ghrelin concentrations,
which remained elevated also over weight maintenance periods of 6 and 12 months [59].
Similarly, long-term exercise intervention
together with diet-control investigations has
demonstrated that total ghrelin levels increase in
response to exercise-induced body weight loss in
obese subjects and not because of food restriction
per se, acting via a negative feedback loop that
regulates body mass [7, 62]. It has been suggested that changes in total ghrelin concentrations appear to be most sensitive to changes in
body mass resulting from overall energy deficit,
independent of specific effects of nutritional
intake and/or physical exercise [7, 62]. There are
studies to demonstrate that manipulations in food
intake and exercise energy expenditure show a
close relationship between circulating ghrelin
196
and energy availability [63, 64]. For example,
Scheid et al. [64] measured total ghrelin, energy
balance and body composition parameters before
and after 3-month intervention period in exercising women and found that circulating ghrelin
does not play a role in the adaptive changes associated with exercise training when exercise
occurs in the absence of body weight loss.
However, fasting ghrelin level increased when
body mass is lost and may respond to even
smaller changes in energy availability [64]. In
addition, the change in total ghrelin level was
inversely correlated with the change in body
mass, body mass index, lean body mass and
energy availability after diet- and exercise-­
associated weight loss [64]. In contrast, no impact
of aerobic training on acylated ghrelin levels was
observed in overweight and obese men [65]. It
has been suggested that differences in body fat
mass loss, exercise volume and duration, and
gender may influence possible differences in
ghrelin responses to weight reduction [59]. In
addition, King et al. [66] showed that equivalent
energy deficits induced by food restriction or
physical exercise have markedly different effects
on appetite, energy intake and acylated ghrelin
concentrations. While food restriction elicited a
rapid increase in appetite and energy intake and
these responses appear to be related to postprandial suppression of acylated ghrelin, acute energy
deficits induced by vigorous intensity exercise
session did not alter appetite or energy intake and
may be related to the failure of acute exercise to
induce compensatory acylated ghrelin responses
[66]. These results together suggest that changes
in body mass are needed before any changes in
circulating ghrelin levels could be seen in
untrained individuals.
Ghrelin Responses to Acute Exercise
There are a number of studies including athletes
that have investigated the influence of acute bout
of exercise on total ghrelin [37, 67–82] and on
acylated ghrelin [66, 83–98] concentrations.
Different investigations with healthy untrained
individuals [37, 67, 68, 78] and also well-trained
J. Jürimäe
endurance athletes [71, 74, 82] would suggest
that exercise-induced acute negative energy balance may not be sufficient to alter total ghrelin
response. Conversely, however, there are studies
demonstrating that total ghrelin level increased
[69, 70, 72, 73] or decreased [75–77, 80, 81] as a
result of short-term exercise session. In addition,
studies with acylated ghrelin have mostly
reported significant suppression [83, 84, 86, 89,
90, 94–98] or no change [66, 85, 92] in measured
acylated ghrelin concentration after acute exercise. However, there are also studies that have
observed significant postexercise increase in
acylated ghrelin concentration [91, 93].
Accordingly, acute exercise studies have demonstrated different responses of different ghrelin
forms to the acute exercise in subjects with different body composition and physical activity
levels.
A study by Dall et al. [68] reported no change
in total ghrelin concentration after acute cycling
exercise for 45 min at the intensity of anaerobic
threshold in healthy middle-aged men. Similarly,
total ghrelin levels remained unchanged after
acute submaximal running workloads (50%,
70% and 90% of maximal oxygen consumption
[VO2MAX]) [78] and also after a single bout of
treadmill running for 60 min [67] in healthy
physically fit male individuals. In well-trained
endurance athletes, a progressively intense intermittent exercise trial on treadmill at different
exercise intensities (10 min at 60%, 10 min at
75%, 5 min at 90% and 2 min at 100% of VO2MAX
[74] and 30 min on-water sculling exercise performed either below or above the intensity of
individual anaerobic threshold [71] did not
change total ghrelin concentration. It could be
argued that acute exercise energy expenditure
was not sufficient to alter total ghrelin response
in these studies [1]. Accordingly, significant
postexercise increases in total ghrelin concentration after prolonged 2-h endurance rowing at the
intensity of 80% of individual anaerobic threshold [34] and after 3-h endurance cycling at the
intensity of 50% of maximal aerobic power [69]
have been observed in endurance-trained athletes. Assuming that the energy balance drives
the ghrelin response to prolonged rowing
12
Ghrelin Responses to Acute Exercise and Training
e­ xercise with the estimated energy expenditure
of 1200–1500 kcal, it was conceivable to see that
the increased postexercise total ghrelin concentration was associated with the amount of work
performed (r = 0.75; p < 0.05) in rowers [34].
Furthermore, it was argued that the reduced resting levels of total ghrelin may have influenced
the significant exercise-induced increase in ghrelin concentration in rowers [34]. The results of
these studies [34, 69] would suggest that a certain threshold reduction in energy availability
should be reached before any significant postexercise increases in total ghrelin concentration
occur and that the amplitude of the total ghrelin
increase could be linked to the energetic status
induced by acute exercise stress and the resting
levels of ghrelin in athletes [1]. However, to
what extent exercise intensity may influence
total ghrelin response to acute exercise has not
yet been determined, although it has been suggested that low- rather than high-intensity exercise with longer duration stimulates total ghrelin
levels [70]. Specifically, Erdmann et al. [70]
investigated the effect of exercise intensity and
duration on total ghrelin release, hunger and
food intake in normal-­weight untrained healthy
individuals. Total ghrelin concentrations were
increased by 50–70 pg/ml as a result of prolonged low-intensity bicycling exercise with a
duration of up to 2 h, while no changes in total
ghrelin were observed during higher intensity
exercise [70]. In addition, only 2-h prolonged
aerobic exercise at the intensity of 50 W with an
exercise energy expenditure of 340 kcal lead to
an increase in food intake without having an
effect on hunger sensations [70]. An increase in
plasma ghrelin concentration during exercise
without alterations of hunger sensations under
similar conditions of low-intensity exercise and
energy expenditure was also found in another
study [79]. Nonetheless, the stimulation of food
intake during prolonged exercise was most likely
not due to changes in circulating total ghrelin
levels [70]. These results together demonstrate
that total ghrelin concentrations can be increased
as a result of a low-intensity prolonged exercise
session when the exercise energy expenditure is
high enough also in untrained subjects.
197
There are studies to suggest that acute exercise stress could also result in a decrease of total
ghrelin concentration [75, 77, 80, 81]. These
studies have used more intensive exercise bouts
including resistance exercise protocols [75, 77,
80, 81], and it has been suggested that glucoregulatory stress from the acute intense exercise could
result in a suppression of circulating ghrelin during the recovery period from the exercise [74,
75]. Indeed, studies that have utilized more intensive exercise bouts have demonstrated that maximal exercise-induced large increases in insulin
[74, 75] and growth hormone [75, 81] levels may
suppress total ghrelin concentration during the
recovery period. However, there are also investigations that contradict the results of these studies
as exercise-induced increases in both total ghrelin and growth hormone values have been
observed after prolonged low-intensity exercise
in endurance-trained males [69] and also in overweight postmenopausal women [79]. Others have
argued that postexercise ghrelin responses may
be independent of changes in energy balance [6]
and that acute exercise stress increases energy
intake only some time postexercise [6, 83]. To
this end, Broom et al. [83] investigated the effects
of 1 h running at 72% of VO2MAX on total and
acylated ghrelin concentrations. They found that
total ghrelin was not changed, while acylated
ghrelin was decreased as a result of exercise [83].
Accordingly, it has been argued that although
there is a close relationship between total and
acylated ghrelin concentrations [25–27], it cannot be excluded that after acute exercise this relationship may be somewhat different [42, 70, 83].
Different studies have demonstrated that relatively high-intensity exercise sessions (≥70%
VO2MAX) may suppress acylated ghrelin concentrations [99, 100]. Typically, this hormonal
decrease coincides with a transient reduction in
appetite during and immediately after the exercise [87, 88], while there are also studies that
have found no changes in appetite as a result of
acute exercise [89, 92, 101]. It is possible that the
lack of commonly observed appetite suppression
may be due to a difference in training status or
fitness of studied subjects [89]. In accordance,
there is an evidence to suggest that highly trained
J. Jürimäe
198
individuals are more accustomed to exercise
stress and therefore do not have as great hormonal, including acylated ghrelin, response to
acute exercise as in untrained individuals [88,
99]. For example, Broom et al. [84] found that
plasma acylated ghrelin and hunger ratings fell
and remained suppressed for 1.5 h after 90 min
running at the intensity of 70% of VO2MAX (≈70%
decrease in acylated ghrelin) in healthy men. In
other studies with endurance-trained men, circulating acylated ghrelin concentrations were
decreased after 45 min of cycling at the intensity
of ≈76% of VO2MAX (≈23% decrease in acylated
ghrelin) [89] and after 20 km run (≈14% decrease
in acylated ghrelin) [90]. Therefore, the suppression of acylated ghrelin in endurance-trained athletes was transient, with concentrations not
different from baseline already after 30 [90] and
40 [89] min postexercise. A recent study by
Mattin et al. [92] observed no significant changes
in acylated ghrelin and appetite scores as a result
of 60 min cycling at the intensities of 40% and
70% of VO2MAX in healthy men. Therefore,
although not statistically significant, acylated
ghrelin responded differently to exercise intensity, as serum levels decreased by ≈27% at the
intensity of 70% of VO2MAX and increased by
≈12% at the intensity of 40% of VO2MAX [92].
Larson-Meyer et al. [91] also found a significant
increase in acylated ghrelin immediately after
60 min running at the intensity of 70% of VO2MAX
in female runners. Therefore, appetite was not
affected by running exercise, and postexercise
acylated ghrelin was not associated with appetite
scores [91]. It was argued that the energy cost of
the running exercise may promote increased
acylated ghrelin secretion after exercise in these
athletes [91]. The results also suggested that acylated ghrelin is not a major contributor to postexercise food intake, perhaps because the signal is
dampened by increases in different anorexigenic
peptides at the same time [91, 102]. In accordance, other studies have also argued that it is
possible that the transient suppression of circulating acylated ghrelin that can be observed during
acute exercise may be entirely unrelated to appetite regulation [50, 85]. These results together
suggest that acylated ghrelin is responsive to dif-
ferent conditions and modes of endurance exercise, duration and intensity, but the direction of
the hormone response can be varied [95]. The differences in acylated ghrelin responses to acute
exercise can also be attributed to subject physical
fitness, pre-exercise meal consumption and timing as well as the timing of the hormone measurements and possible environmental factors
such as temperature and altitude [103]. There is a
need for further investigations to elucidate the
exact mechanisms regulating ghrelin synthesis
and clearance during and after acute exercise.
Chronic Exercise Training
and Ghrelin Responses
Chronic exercise training perturbs energy balance and can potentially alter body mass and
composition. There are a number of studies that
have reported an increase in circulating ghrelin
concentrations after long-term exercise interventions in previously untrained individuals [13, 43,
62, 104–108], while other studies have not found
any changes in ghrelin concentrations as a result
of prolonged exercise training [51, 109–111]. It
appears that circulating ghrelin levels increase
with body weight loss [62, 105, 107, 108] and
decrease with body weight gain [12, 112].
Accordingly, data on ghrelin responses to prolonged exercise training are mainly available
from obese individuals (i.e. individuals involved
in weight loss programme) [62, 106, 107, 109,
113], whereas only limited data are provided for
athletes [29, 30, 114–116]. Most of the previous
investigations have studied total ghrelin response
to prolonged exercise training [13, 29, 30, 43, 62,
108, 109, 114, 115], while relatively few intervention studies have measured acylated [111,
113, 116] or unacylated [23, 24] ghrelin concentrations separately. Currently, there appears to be
only one published study that has investigated the
response of acylated ghrelin to prolonged training period in athletes [116].
Previous investigations have mostly found that
total ghrelin concentrations increase during situations of body weight loss and suggest that weight
loss is the most potential factor influencing ghre-
12
Ghrelin Responses to Acute Exercise and Training
lin response to exercise training [13, 43, 62, 107,
108, 117]. In an earlier study, Leidy et al. [108]
found that fasting ghrelin concentration was
increased twofold in a group of normal-weight
women who experienced weight loss (>1.5 kg) as
a result of a 3-month energy deficit-imposing diet
and 5-days-a-week exercise training intervention
programme [108]. Therefore, body mass, body fat
mass and resting metabolic rate significantly
decreased before the increase in fasting ghrelin
occurred [108]. It was suggested that circulating
total ghrelin responds in a compensatory manner
to changes in energy homeostasis in healthy
young women and that ghrelin exhibits particular
sensitivity to changes in body mass [108]. In
another study, Foster-Schubert et al. [62] reported
that total ghrelin levels increased by 18% in sedentary overweight postmenopausal women who
lost more than 3 kg body mass after 1-year aerobic exercise training programme. Another 1-year
moderate-to-vigorous intensity aerobic exercise
for 45 min 5 days a week demonstrated that
greater weight loss was associated with larger
increases in total ghrelin concentrations in overweight and obese postmenopausal women [107].
Similarly, moderate-intensity aerobic exercise
training 5 days a week for 12 weeks increased circulating acylated ghrelin concentrations in overweight and obese men and women [113]. In
contrast to these findings, fasting acylated ghrelin
concentrations decreased after a moderate dose
(14 kcal/kg body mass weekly) but did not change
after a low-dose (8 kcal/kg body mass weekly)
moderate-intensity aerobic exercise training lasting 4 months in healthy nonobese older women
[111]. It was argued that exercise training dose
can have specific effects on acylated ghrelin that
are not dependent on body weight or body fat
mass loss [111]. However, there was a lack of
acylated ghrelin level change in those participants
who lost body weight or body fat mass as a result
of 4-month training period [111]. In another
study, Ravussin et al. [51] observed that neither
positive energy balance caused by overfeeding
nor negative energy balance induced by exercise
training had a significant effect on total ghrelin
concentration over a 100-day study period. The
impact of negative energy balance on total ghrelin
199
levels at the end of the investigation was smaller,
due to the possible effect of accustomization [51].
Another study with a group of morbidly obese
men and women demonstrated that fasting circulating total ghrelin levels remained unchanged
despite 5% body weight loss induced by a 3-week
integrated body weight reduction programme
with exercise training [109]. The amplitude of
ghrelin response to negative energy balance in
these studies could be linked to the energetic status of studied individuals, which is attributable to
specific body fat mass and exercise training characteristics. Accordingly, data regarding the influence of exercise training programme on circulating
ghrelin in previously untrained individuals suggests that exercise training per se has no impact
on circulating ghrelin levels and changes in ghrelin concentrations that are seen as a result of exercise training intervention take place as secondary
changes to body weight loss [117].
Evidence suggests that the degree of negative
energy balance and/or body weight loss threshold to increase circulating ghrelin concentrations
has not yet been determined [1, 17]. In heavily
exercising females, menstrual disturbances have
been linked to an energy deficiency, where
caloric intake is inadequate for exercise energy
expenditure [12, 118]. These menstrual disturbances, together with an energy deficiency, are
largely attributable to athletic events, where the
emphasis is on the achievement of thin and lean
physiques, which may require low body mass
and body fat percent such as in gymnastics, figure skating and long-distance running [12].
Accordingly, higher ghrelin levels have been
observed in amenorrheic athletes than in normally ovulating women who train [17, 119]. In
fact, there are data to suggest that young female
athletes with varying severities of menstrual disturbances can be distinguished from each other
based on their circulating ghrelin levels [12, 48,
120, 121]. To this end, as energy deficiency
increases in severity across the continuum of
menstrual cycle disturbances, physically active
women with amenorrhea have the lowest resting
energy expenditure relative to lean body mass,
together with the increased ghrelin levels [48,
121]. In contrast, physically active women with
200
subtle menstrual disturbances and nonathletic
controls present higher resting energy expenditure relative to lean body mass and lower ghrelin
concentrations [48, 121]. Increased ghrelin levels in young female athletes with amenorrhea
may have a role in reproductive system [12, 119,
120]. An inverse relationship between acylated
ghrelin concentration and gonadal steroids was
observed in athletes [48], and acylated ghrelin
levels may differentiate between athletes who
will or will not develop functional hypothalamic
amenorrhea during heavy training [48, 119].
Accordingly, it is likely that high circulating
ghrelin concentrations contribute to functional
hypothalamic amenorrhea by altering gonadotropin-releasing hormone and luteinizing hormone pulsatility [119, 120]. Therefore, body fat
mass has an important negative influence on
basal ghrelin levels in amenorrheic athletes [48,
120]. An increase in energy intake in amenorrheic athletes induces a decrease in basal ghrelin
concentrations, which is paralleled by increases
in body mass and resumption of menses [119].
Accordingly, it appears that circulating ghrelin is
a biomarker of energy imbalance across the
menstrual cycle in female athletes [36, 122].
Since ghrelin levels are consistently elevated in
energy deficiency such as functional hypothalamic amenorrhea, ghrelin could be an important
marker of energy deficiency and chronic undernutrition [12] and should be measured to monitor the health of female athletes.
The mechanisms by which changes in energy
balance and/or body mass impact on circulating
ghrelin levels are not fully understood [2, 36,
117]. It has been proposed that leptin, which levels directly correlate with body fat mass, may
have an influence on circulating ghrelin concentrations [117]. Specifically, a negative association
between circulating leptin and ghrelin concentrations has been reported [34], and an increase in
circulating ghrelin levels in response to body
weight loss may therefore occur as a result of a
decrease in circulating leptin concentrations
[117]. Therefore, alterations in ghrelin levels as a
result of changes in body fat mass may therefore
be secondary to changes in leptin [117]. In addition, insulin may also mediate some of the effects
J. Jürimäe
of body adiposity on circulating ghrelin [117] as
circulating ghrelin concentrations are inversely
correlated with insulin and insulin resistance values [123]. It has been suggested that relatively
low ghrelin concentrations observed in obese
individuals may be a result of insulin resistance
that is a characteristic in obesity and which has
an inhibitory effect on ghrelin concentrations,
rather than excess body mass by itself [123].
Collectively, this may represent one mechanism
by which insulin is implicated in the homeostatic
regulation of energy balance [117].
Only few studies have investigated ghrelin
response to different exercise training periods in
adult male [30, 114–116] and female [29] athletes.
Specifically, in male athletes, ghrelin responses to
a weight reduction period before competitions in
bodybuilders [30], an intensive training camp in
football players [116] and a high-volume lowintensity endurance [114] and a high-volume lowintensity concurrent endurance and resistance
[115] training periods in competitive rowers have
been studied. In addition, ghrelin responses to
intensified training period were also studied in
female synchronized swimmers [29]. While studies with national-level male bodybuilders [30] and
international-level female synchronized swimmers [29] demonstrated that total ghrelin levels
increased together with a body weight reduction as
a result of negative energy balance, no differences
in total ghrelin concentrations together with no
changes in body mass values were observed in
competitive male rowers as a result of increased
training volume [114, 115]. Accordingly, it can be
speculated that body weight loss is also important
to reduce total ghrelin concentrations in studied
athletes. In contrast, circulating acylated ghrelin
concentrations were significantly lowered during
the 9-day intensive training camp, which tripled
the training volume in male college-level footballers [116]. Therefore, no changes in body mass
values were observed, and an increase in physiological stress was associated with a decrease in
appetite [116]. It was suggested that an earlyphase physiological stress response may decrease
the acylated ghrelin concentrations in male athletes during an intensive training camp [116]. The
reason for different results between this study with
12
Ghrelin Responses to Acute Exercise and Training
other studies in athletes is not clear. It is possible
that these discrepancies are due to factors related
to the different modes of exercise, energy availability and competitive level of athletes. However,
it is also likely that differences in dietary control,
sample collection and assay procedures may also
be implicated [117]. Clearly, further studies with
elite athletes with different training programmes
are needed before any definitive conclusions can
be drawn.
Relative to women athletes, a national team of
female synchronized swimmers performed a
4-week intensified training period, where a baseline training load of about 22 h was increased by
a 20.5% across the intensified training period,
which caused a significant decrease in body fat
percent from 17.3% to 16.4% in these elite female
athletes [29]. In addition, a decrease in energy
availability was observed, which was accompanied by an increase in ghrelin and decrease in
leptin, reflecting a decrease in energy stores across
the investigation period [29]. The results of the
Schaal et al.’s [29] study demonstrate that a state
of an increased fatigue and rather low energy
availability in these elite female athletes was characterized by a significant increase in ghrelin levels
shortly before the season’s target competitions.
Accordingly, it may be suggested that an increased
ghrelin concentrations can be used as a marker of
increased training stress and inadequate energy
availability in elite female athletes.
In a study with male bodybuilders, 14 athletes
were divided into seven competitors and seven
control athletes, who were followed for 11 weeks
before the national championships [30].
Competitors were able to significantly decrease
their mean body mass by 4.1 kg during the
11-week period, whereas no changes in body
composition or ghrelin values were observed in
the control athletes [30]. In competitors’ group,
the energy deficit at about 536 kcal/day after the
first 5-week period was already sufficient to
cause a significant increase in total ghrelin concentrations, whereas no further increase in ghrelin levels was observed with the energy deficit
reaching 978 kcal/day after 11-week preparatory
period [30]. The athletes in the present investigation were competitive bodybuilders with a mean
201
body fat percent of 9.6% at the beginning of the
study and 6.5% at the end of the study [30]. It
was argued that ghrelin secretion might have
reached its limits at some point, and the negative
energy balance of more than 900 kcal/day and a
significant body weight loss of 2.4 kg in the second 5-week training period (between weeks 6
and 11) were not sufficient to further the significant total ghrelin increase in these athletes [30].
It was concluded that circulating ghrelin levels
increase in well-trained bodybuilders with relatively low body fat percent but reach a plateau
beyond which there is no further increase in total
ghrelin levels, despite continuing negative energy
balance and body weight loss [30].
In studies with male rowers, total ghrelin concentrations were measured after a reference week
with usual training volume, after 2 weeks of
high-volume training and after a recovery week
with reduced training volume [114, 115]. In the
first study, 90% of the trainings (rowing, running
or cycling) were aerobic type of exercise and
only 10% resistance type of exercise [114], while
in the second study about 50% of the trainings
were low-intensity resistance exercise and 50%
aerobic type of exercise [115]. It appeared that
fasting ghrelin concentrations were not increased
as a result of the 2-week period of extended training volume in both studies [114, 115], while a
decrease in fasting ghrelin was observed after a
recovery week [115]. Although energy intake and
energy expenditure increased significantly, the
negative energy balance after the 2-week period
of high-volume training and energy restriction
was about 455 and 408 kcal/day in endurance
[114] and concurrent resistance and endurance
[115] training studies, respectively. It could be
argued that during specific metabolic conditions
resulting from the preceding high-volume training period with high energy expenditure, negative energy balance, temporarily restricted caloric
condition in fasting state and probably relatively
low body energy stores (i.e. low body fat percent)
may all contribute to further exercise-induced
effects on energy expenditure that leads to
­downregulation of ghrelin concentration in male
rowers [114, 115].
202
Conclusions and Future Directions
Energy homeostasis is regulated by a neuroendocrine system that also includes different appetite
hormones including ghrelin. Ghrelin concentrations decrease during growth and pubertal maturation and are linked to nutritional status, with
lower levels in obese and higher levels in underweight individuals. Therefore, basal ghrelin levels are elevated in growing athletes, while
pubertal onset decreases ghrelin levels even in
the presence of chronically elevated energy
expenditure in young athletes. Since increased
participation of children in competitive sport is
evident, more research on the exercise-induced
modification of the appetite hormones including
ghrelin is warranted. It has to be considered that
in those sport disciplines where heavy training
with large energy expenditure starts at a relatively young age, there is a greater risk for developing the female athletic triad already during
adolescent period. It can be suggested that growing and maturing athletes should be monitored at
short intervals to better understand the influence
of high athletic activity on hormonal markers
including ghrelin that are involved in overall
growth and energy homeostasis. Ghrelin can be
used as an indicator of energy imbalance across
the menstrual cycle in female athletes. Elevated
ghrelin concentrations have been observed in
female athletes with chronic energy deficiency,
and ghrelin may differentiate between athletes
who will or will not develop functional hypothalamic amenorrhea and be at risk for Relative
Energy Deficiency Syndrome in Sport (RED-S).
In addition, most of the investigations have studied the role of ghrelin in energy availability in
different groups of obese individuals, while less
studies have been done with athletes to investigate the possibility to use circulating ghrelin as a
possible marker of training stress.
The current available information regarding the
role of different forms of ghrelin concentrations in
energy balance during acute exercise and prolonged training stress is not entirely clear. Acute
exercise studies have demonstrated varied
responses of different ghrelin forms to the acute
exercise in individuals with different body compo-
J. Jürimäe
sition and physical activity levels. Various investigations with healthy untrained individuals and also
well-trained endurance athletes would suggest that
exercise-induced acute negative energy balance
may not be sufficient to alter total ghrelin and/or
acylated ghrelin response. There are also studies
that have argued that a certain threshold reduction
in energy availability should be reached before any
significant postexercise increases in total and/or
acylated ghrelin levels occur and that the amplitude of the ghrelin increase could be linked to the
energetic status induced by acute exercise stress
and the resting levels of ghrelin in athletes.
However, to what extent exercise intensity may
influence circulating ghrelin response to acute
exercise has not yet exactly been determined,
although it has been suggested that low- rather
than high-intensity exercise with longer duration
stimulates ghrelin response. In contrast, different
studies with acylated ghrelin have mostly reported
significant suppression in measured acylated ghrelin concentration when performed at higher intensities. Therefore, the transient suppression of
circulating acylated ghrelin that can be observed
during acute exercise may be entirely unrelated to
appetite regulation. The differences in ghrelin
responses to acute exercise can be attributed to
subject physical fitness, pre-exercise meal consumption and timing, the timing of the hormone
measurements as well as sampling processing and
assay protocols. Additional research is needed to
elucidate the exact mechanisms regulating ghrelin
synthesis and clearance during and after acute
exercise.
Results regarding the influence of exercise
training programme on circulating ghrelin are
more consistent and mainly suggest that exercise
training per se has no impact on circulating ghrelin levels, and changes in ghrelin concentrations
as a result of exercise training intervention take
place as secondary to body weight loss. Therefore,
the majority of training studies have investigated
the responses of total ghrelin concentrations,
with relatively less studies measuring acylated
ghrelin separately. Typically, circulating ghrelin
levels increase with body weight loss and
decrease with body weight gain. Data on ghrelin
responses to prolonged exercise training are
12
Ghrelin Responses to Acute Exercise and Training
mainly available from obese individuals, whereas
only limited data are provided for athletes. It has
been suggested that there is a negative energy
balance and/or body weight loss threshold to
increase circulating ghrelin concentrations that
has not yet been exactly determined. It appears
that basal and postexercise ghrelin responses
without altering body mass are not sensitive
enough to represent changes in training volume
and energy availability in athletes. There is also
some evidence to suggest that although ghrelin
increases together with body weight loss in
highly trained athletes with already relatively low
body fat mass, there may be a plateau beyond
which there is no further increase in circulating
ghrelin concentrations despite continuing negative energy balance and body weight loss. Further
investigations are needed to describe the exact
role of ghrelin at different training conditions in
athletes representing different sport events.
Collectively, additional research including longitudinal studies in different populations with various body composition and physical activity
patterns is warranted to better describe the role of
ghrelin and its specific forms in conditions of
energy deficiency, surplus and balance.
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Hormonal Regulation of Fluid
and Electrolyte Homeostasis
During Exercise
13
Charles E. Wade
Introduction
In response to exercise, there are numerous alterations in fluid and electrolyte homeostasis. These
perturbations occur immediately upon initiation
of exercise and can persist for hours or even days
after completion of exercise. The endocrine system plays an important role in the regulation of
fluid and electrolyte homeostasis that must occur
with exercise. Dysregulation of the endocrine
system may limit exercise activity and, in some
incidences, result in debilitating morbidities or
death. This chapter emphasizes responses to
exercise and reviews the importance and factors
involved in the maintenance of fluid and electrolyte balance. Previous reviews will be used to
address the basics of effected systems; however,
emphasis is placed on new data and the current
discussions about performance of work and
exercise.
The term exercise is an ambiguous term covering a broad range of physical activities. The
term is employed to define activities such as running and cycling but is also used to cover the
activities of daily living and work. Thus, when
discussing responses to exercise, it is important
to clarify the type of activity, the level at which it
C. E. Wade (*)
Center for Translational Injury Research (CeTIR),
Houston, TX, USA
e-mail: charles.e.wade@uth.tmc.edu
is performed, and the duration. In defining the
responses to exercise, it is essential to understand the definitions of workload. The absolute
workload is the level of exercise being performed, such as running on a treadmill at a
defined speed. For individual subjects, this
would produce a variable response depending on
their level of fitness/training. Therefore, to compare exercise responses between subjects, relative workload is often employed as a
normalization technique [1–3]. Relative workload is expressed as a percentage of the maximum capability of the individual to perform that
specific exercise and is often further standardized to the heart rate or oxygen consumption of
the subject.
Physiologic Responses to Exercise
A variety of conditions results from alterations in
fluid and electrolytes and affects the performance
of exercise and work. The disruption of the balance of fluids and electrolytes correlates with
limitation of work capacity; however, the range
of changes tolerated may be extended with training and repeated exposures. In general the body
can undergo one of several responses to exercise: dehydration, dysnatremia, hypovolemia, or
hypervolemia. The following text will review
each.
Dehydration is defined as a reduction in total
body water (TBW) and an increase in plasma
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_13
209
C. E. Wade
210
electrolyte concentrations. Heavy exercise and
extreme heat are two of the most prevalent
causes of dehydration, as both are associated
with exercise and subsequent loss of fluid volume due to sweating and inadequate fluid intake
[4–7]. Current evidence suggest that dehydration resulting in a decrease of greater than 2%
body mass will adversely affect exercise performance [6–8]. However, decrements in selfpaced exercise may not occur until a 4% loss in
body weight [9]. Regardless of the level of
dehydration, a loss of TBW and an increase in
plasma electrolyte concentrations are associated
with limited work performance and, in extreme
cases, death.
Dysnatremia covers the occurrence of both
increases and decreases in plasma sodium
observed with exercise [10–14]. Siegel et al.
noted an incidence rate of dysnatremia of 32.5%
in 1319 collapsed marathon runners [12]. Of
these, 85% were hypernatremic and 15% hyponatremic. Both of these conditions have been
associated with deaths in competitive runners.
Hypovolemia is a decrease in blood volume
in the absence of changes in plasma electrolyte
concentrations. This can occur with exercise or
hemorrhage [15] and follows periods of water
submersion to the neck or the administration of
diuretics commonly used in the treatment of
hypertension [16, 17]. Hypovolemia necessitates an increase in heart rate at submaximal
workloads and a more rapid increase in body
temperature, both indicative of limited work
performance [7].
In contrast, hypervolemia is the expansion of
blood volume. There is extensive literature on the
expansion of blood volume by increasing the red
cell mass; however, within the scope of this chapter, this term refers to expansion of the plasma
volume. Plasma volume is expanded by exercise
training and by acute excessive ingestion of fluids, hyperhydration [7, 18–20]. Warburton et al.
reviewed the literature on the effect of acute
expansion of plasma volume and found minimal
increases in maximum oxygen consumption, but
there were negligible changes in exercise endurance [20].
Modulation of Hormones
in Responses to Exercise
Workload Intensity
The response of hormones to exercise is closely
related to the amount of relative work performed.
There are three basic patterns of hormones during exercise. The first is an increase proportional
to the increase in relative workload. For example,
with each increase in workload, there is a constant increase in the plasma hormone concentration of atrial natriuretic peptide (ANP)
(Fig. 13.1a). The second pattern is a logarithmic/
exponential increase such as that reported for
plasma renin activity (PRA) (Fig. 13.1b). With
increasing workloads, the level of hormone
increases at an exponentially faster rate. The third
pattern is related to an onset of an increase at a
given threshold; this is observed for vasopressin
(Fig. 13.1c). A threshold response for exercise is
usually associated with the onset of anaerobic
metabolism and a relative workload of about
70%. This has also been associated with the
increase in stress-related hormones such as cortisol and adrenocorticotropic hormone (ACTH).
These patterns of increased hormone concentrations are consistently observed in studies of acute
exercise when the response is expressed relative
to the workload of the task performed.
Exercise Duration
The duration of exercise is also a confounding
factor in the response of hormones to exercise.
Extended time, rather than intensity, may have a
greater influence on the levels of hormones during exercise. This is especially true of hormones
involved in the regulation of fluid and electrolyte
homeostasis. As exercise progresses, there is an
increased metabolic heat necessitating sweating
and therefore the loss of water and electrolytes.
The increase in aldosterone, which regulates
sodium balance, is increased twofold with acute
maximal exercise (i.e., running on a treadmill)
and returns to baseline levels within an hour.
13
a
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
b
Linear
300
211
Logarithmic/Exponential
1500
PRA% Resting
ANP% Resting
250
200
150
100
1000
500
50
0
0
0
50
0
100
100
% Workload
% Workload
c
50
Threshold
AVP% Resting
1500
1000
500
0
50
0
100
% Workload
Fig. 13.1 The various patterns of response of hormones
to exercise. The individual dots represent the response
from independent studies of exercise on a cycle ergometer
with varying workloads. The variance represents differences in how the exercise was performed, state of hydration of the subjects, and difference in assay techniques.
With these confounders the patterns in response to exercise are still present. The linear example is demonstrated
by the response of atrial natriuretic peptide (ANP; (a) 11
studies), the logarithmic/exponential increase by plasma
renin activity (PRA; (b) 20 studies), and the threshold
response by vasopressin (AVP; (c) 23 studies)
Extended exercise times elicit similar changes in
plasma volume and sodium concentrations, but
aldosterone concentration increases three to four
times the basal levels and remains elevated for
over 24 h [21]. The greater and enduring response
to exercise of longer duration is postulated to be
due to additional regulators associated with the
“stress” of exercise [10, 22]. Of note, hormone
concentrations may vary over time with exercise
of long duration, such as during a marathon or
ultra-endurance events. For example, ANP is
increased by a factor of ten during the first 10 km
of a marathon but subsequently decreased to levels only fivefold greater than baseline [23]. In
addition, the conditions under which recovery is
conducted, access to fluids or cool down exercise, are influential in the postexercise responses
and need to be clarified [24, 25]. Recently, Hew-­
Butler et al. compared the hormonal responses to
maximal exercise with a mean duration of
10–60 min of exercise at a treadmill speed equivalent to 60% of the maximum [26]. With maximal acute exercise, significant increases were
reported for vasopressin (5-fold) and aldosterone
C. E. Wade
212
(2-fold), while at submaximal effort, only aldosterone was increased (3.3-fold). Thus, both the
length of time and intensity of the workload must
be considered when studying the regulation and
function of hormones in response to exercise.
Training
The level of training of a subject may influence
the hormonal response to exercise [27, 28]. While
much of the variance between subjects at absolute workloads may be due to differences in the
relative workload being performed, there are still
aspects of training that change the response.
Individuals undergoing persistent heavy bouts of
exercise training may have alterations in resting
levels. In subjects doing daily long-distance runs,
plasma aldosterone concentrations are elevated
compared to controls [29]. However, for the
majority of hormones regulating fluid and electrolyte homeostasis, training does not appear to
be as an important of a factor as the intensity and
duration of exercise in the response of these
hormones.
Hydration Status
The initial hydration status of a subject may
influence subsequent responses to exercise. Fluid
intake during the performance of exercise is also
an influencing factor. Dehydration or hyperhydration alters initial hormone levels; however, the
subsequent response to exercise appears independent. Geelen et al. found that following dehydration, ingestion of fluid caused a rapid and
pronounced reduction in vasopressin and an
increase in norepinephrine that was independent
of changes in plasma osmolality and volume
[30]. No changes were noted in epinephrine,
aldosterone, PRA, or ANP. Additional investigations reported that the greater the volume consumed, the more pronounced the decrease in
vasopressin and increase in norepinephrine [24,
31–33]. This suggests an oropharyngeal reflex
may be present and mediated by the sympathetic
nervous system.
Khamnei et al. evaluated the effect of the combination of exercise and postexercise fluid intake
on vasopressin [24, 32]. Subjects exercised at
50% of their maximum oxygen uptake for 30 min.
Exercise resulted in a 45% increase in vasopressin
which was sustained after exercise in the absence
of fluid intake. In contrast, when a large volume of
fluid was ingested after exercise, control levels of
vasopressin were obtained within 3 min. These
findings suggest fluid intake may have a profound
effect on hormonal responses during exercise,
independent of changes in plasma volume and
osmolality. Hew-­Butler has put forth the hypothesis that inappropriate increases in vasopressin
during prolonged exercise in the presence of adequate fluid intake may be a contributing factor to
hyponatremia and subsequent morbidity [10, 22].
This line of research awaits additional well-controlled prospective studies to fully identify underlying mechanisms.
Sex
Sex of the subject is another factor with demonstrated differences. In women, the phase of the
menstrual cycle in which exercise is performed
may alter the hormonal responses. Resting aldosterone levels are increased during the mid-luteal
phase of the cycle, and the response to exercise is
amplified [34]. Further work by Stachenfeld and
coworkers has demonstrated the effect of progesterone and estrogen on the levels and responses
of hormones that are important in fluid and electrolyte homeostasis [35, 36]. In patients with
coronary heart disease, basal levels of vasopressin were elevated in men; however, in responses
to a 6 min walk test that increased vasopressin,
ANP, norepinephrine, and epinephrine, there
were no differences between males and females
[37]. Following exercise in well-trained subjects
to decrease body mass by 3%, women had a
lower PRA and faster recovery of aldosterone
and slower recovery of vasopressin compared to
men [38]. Overall, there are minimal differences
reported between male and females in resting
hormone levels, and differences in response to
exercise are not fully delineated [39].
13
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
213
Health Status
Other Influencing Factors
The initial health of the subject is an influencing
factor in the hormonal responses to exercise and
offers insights to the pathophysiology of various
disease processes and in some cases a means of
diagnosis and/or rehabilitation. The presence of
disease represents a shift in homeostasis that
requires alteration in the responsiveness of hormones important in fluid and electrolyte homeostasis. In age-matched subjects, Shim and
coworkers reported that subjects with an exaggerated blood pressure response to exercise, which is
indicative of a greater risk for hypertension and
prevalence of cardiac hypertrophy, had elevated
levels of angiotensin II at rest and an augmented
increase in response to exercise [40]. However,
there were no significant differences in norepinephrine, epinephrine, PRA, or aldosterone at the
end of exercise. Kjaer et al. studied patients with
congestive heart failure (CHF) and compared
them with healthy subjects at 50 and 75% of their
maximum workloads on a cycle ergometer [41].
Basal levels of ANP, brain natriuretic peptide
(BNP), vasopressin, and PRA were elevated in
patients with CHF. In response to exercise, ANP,
arginine vasopressin (AVP), norepinephrine, and
epinephrine were all increased in both groups.
Even though higher absolute levels were observed
in subjects with CHF, when expressed as a percent of basal concentrations group, differences
were negated. BNP was increased with exercise
only in patients with CHF.
Coiro et al. assessed the response of vasopressin to exercise to exhaustion on a bicycle ergometer in subjects with diabetes and controls and
further segregated the groups as smokers and
nonsmokers [42]. Baseline vasopressin concentrations at rest (2.1–2.6 pg/mL) were not different
between groups. In all groups, there was a significant increase in vasopressin in response to exercise. While smoking was not identified as a
contributing factor, there was a greater increase
in vasopressin in subjects with diabetes (12–
13 pg/mL) than controls (7–8 pg/mL). The difference between diabetic and normal subjects could
not be attributed to cardiovascular or respiratory
responses.
Other confounders, such as position of exercise
and age, have been identified to influence hormonal responses to exertion. Wolf et al. compared supine and upright exercise on a cycle
ergometer at a relative workload of 40–50% for
20 min. With supine exercise, the response of
PRA and aldosterone to exercise was increased
by 90% and 49%, respectively, in contrast to
upright exercise [43]. These differences
occurred in the absence of difference between
the types of exercise in plasma osmolality or
blood pressure. Perrault et al. found ANP concentrations to be increased and vasopressin,
PRA, and norepinephrine to be reduced, during
supine exercise on a cycle ergometer in comparison to exercise in an upright position [44].
During the performance of a marathon, subjects
with a mean age of 47 years had an increase in
ANP to 104 pg/mL compared to 43 pg/mL in
younger subjects with a mean age of 28 years
[23]. In addition, differences in hormone concentrations reported in response to exercise may
be in part explained by the differing methods of
measurement. The presence of such confounders in the comparison of the hormonal responses
to exercise has not been systematically
addressed, partially limiting our interpretation
of the role of hormones in fluid and electrolyte
homeostasis during exercise.
Hormone Responses to Exercise
The hormones of consequence to fluid and electrolyte balance in exercising humans are those
involved in the regulation of thirst and function
of the kidneys and sweat glands. The essential
hormones are the catecholamines, vasopressin,
the renin-angiotensin-aldosterone system, and
natriuretic peptides. While these hormones have
a variety of functions, the focus of the present
review will be on their responses to exercise and
impact on fluid and electrolyte homeostasis
­during and following exercise. Circulating levels of these hormones are altered during exercise as a function of changes in secretion,
C. E. Wade
214
metabolism, and volume of distribution. The
most common measurement of these hormones
in association with exercise is the circulating
concentrations, which will be the focus of the
present effort.
Catecholamines
Catecholamines, specifically norepinephrine
and epinephrine, are derived from increases in
sympathetic nervous system activity and the
adrenal glands [45, 46]. The kidneys are also
suggested as a source of norepinephrine [47].
Levels of circulating catecholamines respond
rapidly upon the onset of exercise in order to
redistribute blood flow to meet metabolic
demands [2, 48, 49]. In response to exercise,
there is a progressive increase in circulating
norepinephrine levels from 1.3 to 3.0 nmol/L at
rest to 12.0 nmol/L following maximal exercise
[45, 50–52]. The increase in epinephrine occurs
later in the course of exercise and can rise from
resting levels of 380–655 pmol/L to concentrations over 3000 pmol/L. The increase in the
ratio of norepinephrine to epinephrine demonstrates activation of the sympathetic nervous
system and is attributed to active spillover from
the muscles during exercise [45, 52–54]. With
continued exercise, there is an attenuation of the
increase in the ratio of norepinephrine to epinephrine, which is indicative of an increase in
the release of epinephrine predominately from
the adrenal medulla under the control of hypothalamic mediation in addition to the sympathetic nervous system. Following exercise,
plasma levels of catecholamines return to resting levels in a matter of minutes, as they have a
short half-life due to degradation and reuptake
by the sympathetic nervous system. Recent
studies that inhibited the reuptake of norepinephrine have demonstrated an increase in the
time necessary to complete work equal to
30 min of exercise at 75% of maximal workload
[55, 56]. These studies suggest clearance from
the circulation of norepinephrine plays a role in
fatigue.
Vasopressin
AVP is also known as vasopressin or antidiuretic
hormone (ADH). It is a neurohypophysial hormone synthesized in the hypothalamus and stored
in the posterior pituitary [57, 58]. Vasopressin is
a pressor that alters peripheral resistance, but its
greatest effect is on the reabsorption of water in
the collecting tubules of the kidneys. Secretion of
vasopressin is regulated by alterations in plasma
osmolality and blood pressure. Circulating concentrations of vasopressin in humans are 1–4 pg/
mL [57, 59–62]. With maximal exercise, vasopressin concentrations of 4–24 pg/mL are
reported. Maximum conservation of water by the
kidneys is observed at vasopressin levels of
10–20 pg/mL. With progressive increases in
exercise, elevation of vasopressin is not observed
until 70% of maximum workload is attained, i.e.,
the anaerobic threshold (Fig. 13.1c). Animal
experiments have demonstrated an increase in
activation of hypothalamic neurons that is indicative of increased vasopressin content (production) and of performing above the anaerobic
threshold [63]. Thus, the response of vasopressin
appears to be associated with the onset of anaerobic metabolism, which is also related to increases
in “stress hormones” such as cortisol and
ACTH. An increase in vasopressin may persist
for over 60 min after exercise or longer if access
to fluids is restricted. Of note, at low workloads
of about 25% of the anaerobic threshold, vasopressin decreases have been reported.
A variety of factors have been demonstrated to
mediate the increase in vasopressin with exercise,
including the increase in osmolality and reduction in intravascular volume; however, the
increase in plasma osmolality appears to be the
primary mediator (Fig. 13.2) [59, 64, 65]. In subjects exercising at 65% of maximum while running on a treadmill, there was a progressive
increase in vasopressin with progressive workloads [66]. In subsequent tests which involved
dehydration that decreased body weight by 3 and
5%, resting vasopressin levels were increased in
association with the decrease in blood volume;
however, in response to exercise, further increases
13
a
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
b
AVP
10
Thirst
Very, very 7
thirsty
6
8
5
6
Thirst
Plasma AVP
215
4
4
3
2
2
1
0
275
285
295
Not thirsty 0
280
Plasma Osmolality (mosmol/kg–1)
285
290
295
Plasma Osmolality (mosmol/kg–1)
Fig. 13.2 (a) Levels of vasopressin and (b) subjective
assessment of thirst in association to plasma changes in
osmolality during moderate exercise. Measurements were
from subjects with different levels of fitness, under various levels of hydration. (Redrawn from Merry et al. [27])
in vasopressin were related to the magnitude of
the increase in osmolality. Brandenberger et al.
evaluated rehydration during exercise giving subjects no fluids, water, or an isotonic solution.
Intake of water reduced osmolality but did not
alter plasma volume [67]. Consumption of the
isotonic solution did not change osmolality but
increased plasma volume. Both methods of rehydration decreased the rise in vasopressin levels
with exercise, as well as those of PRA and cortisol. Others have reported similar findings [32, 44,
68]. The independence of the increase in osmolality and blood volume, and the regulation of
vasopressin in response to exercise, is similar to
that reported with dehydration. Coiro and colleagues have demonstrated that the increase in
vasopressin during exercise to exhaustion may be
attenuated by blockade of 5-HT3 serotonergic
receptors and administration of somatostatin,
supporting another means of mediating the
increase in vasopressin during exercise [69].
Recently, Hew-Butler et al. have questioned the
relationship of vasopressin and plasma osmolality during exercise. In subjects participating in an
ultramarathon, they observed 3.9-fold increase in
plasma vasopressin, no significant change in
plasma sodium, and a significant decrease in
plasma volume [10, 22]. They also evaluated
cyclists during a 109 km race and observed nearly
identical changes [70]. In subjects participating
in an ultramarathon, they observed a 3.9-fold
increase in plasma vasopressin in the absence of
a significant change in plasma sodium though
plasma volume was significantly decreased.
These authors and others hypothesize that under
conditions of prolonged exercise, the osmotic
regulation of vasopressin is overshadowed by
non-osmotic stimuli, of which, the reduction in
blood volume plays a minor role [14, 71, 72]. The
increase in AVP was associated with elevations in
cortisol, oxytocin, and BNP, which underscores
the relationship of AVP release with “exercise
stress.” Irrespective of the means, vasopressin is
elevated by more than fourfold during acute exercise to exhaustion or intense prolonged exercise.
Renin-Angiotensin-Aldosterone
The renin-angiotensin-aldosterone systems are
closely coupled and increased in response to
exercise. Renin is released from the kidney in
response to sympathetic nerve stimulation, as
well as norepinephrine spillover, resulting in
C. E. Wade
216
Natriuretic Peptides
Peptides demonstrated to elicit a natriuresis have
been deemed natriuretic peptides. These include
ANP, BNP, urodilatin, and adrenomedullin.
300
Urinary Na+ Excretion (µmol/min)
increased plasma concentrations [17, 45, 52, 73–
76]. Renin then converts angiotensinogen to
angiotensin I, which is subsequently transformed
to angiotensin II in the lung. Angiotensin II promotes the release of aldosterone from the adrenal
gland.
With exercise, all aspects of this system are
increased and play a variety of roles in the regulation of fluid and electrolyte homeostasis [3, 45,
60, 77, 78]. At rest, PRA has levels in the order of
0.15–0.55 ng angiotensin I/mL/h and with maximal exercise increases to levels of 1.11–1.67 ng
angiotensin I/mL/h. There is an exponential
increase in renin activity with increasing workloads; significant differences are reported at levels of 60–70% of maximum (Fig. 13.1b). The
increase in PRA with exercise is positively associated with the increase in angiotensin II. Basal
levels of angiotensin II are 15–25 ng/L, with values of 130–160 ng/L achieved with maximal
exercise. Aldosterone release is regulated by
angiotensin II, as well as ACTH and the plasma
levels of sodium and potassium. Aldosterone
concentration increases from resting levels of
80–830 pmol/L to concentrations of 250–
3330 pmol/L with maximal exercise. Blockade of
the conversion of angiotensin I to angiotensin II
does not attenuate the response of aldosterone to
maximal exercise, which supports the theory that
other pertinent regulatory factors are involved
[79, 80]. The elevation of aldosterone may persist
for days after exercise, and levels are dependent
upon the sodium and water intake [21]. In the
postexercise period, the increase in aldosterone
may be the product of increased water intake,
which reduces the plasma sodium concentration
or the persistent elevation of aldosterone—which
is due to activation of the ACTH. Irrespective of
the cause, the increase in aldosterone due to exercise plays a role in the conservation of sodium in
the sweat glands and kidneys (Fig. 13.3).
250
200
150
100
50
0
0
200
400
600
Plasma Aldosterone (pg/mL)
Fig. 13.3 Plasma aldosterone concentrations were compared to the urinary excretion of sodium at the end of a 2 h
run (closed circles) and following 48 h of recovery with
food and water ad libitum (open circles). With exercise,
there was an increase in aldosterone, and over the recovery period, there was a decrease. (Adapted from Wade
et al. [29]))
These peptides appear to participate in the regulation of fluid homeostasis by protecting against
volume and pressure overloads. Though these
peptides have been extensively studied over the
past 30 years in patients with disease such as
heart failure, pulmonary hypertension, and
chronic renal disease, their response to and role
during exercise are not well defined.
Additionally, well-designed studies in control
subjects or during competitive events have yet
to be undertaken.
trial Natriuretic Peptide
A
ANP is increased with exercise in a linear
response (Fig. 13.1a). Resting plasma levels of
10–49 pg/mL are increased to over 100 pg/mL
with acute maximal exercise [22, 25, 39, 44, 81,
82]. In response to long-duration exercise, there
is initially a pronounced increase, a subsequent
fall, and then a re-elevation of levels, persisting
until completion of the exercise [23]. Resting
levels are obtained within hours of cessation of
the activity [77]. The primary stimulus for the
increase in ANPwith acute exercise is an
increase in atrial stretch due to an increase in
venous return [62]. However as exercise progresses, atrial pressure decreases as blood flow is
13
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
redistributed (cardiovascular drift) to meet the
metabolic demand of active tissues and to dissipate the thermal load [48, 49]. The response of
ANP to extended exercise may be increased if
water is ingested, suggesting a fluid volume
change directly on the heart mediating release
[83, 84]. Recently, pronounced increases in ANP
with exercise have been associated with increases
in cardiac troponin levels, suggesting myocardial
damage during heavy exercise could be a contributing factor to increases in ANP [85]. In cardiac
transplant patients, ANP levels are elevated, and
the response to exercise is accentuated. This suggests that in normal subjects with naturally innervated hearts, there may be neural inhibition of
ANP release [44, 86, 87]. Support for this hypothesis is the observation in patients with hypertension that chronic beta-blockade substantially
increases the ANP response to exercise [88].
Sodium intake appears to also affect the ANP
response to exercise [89, 90]. During submaximal cycle ergometer exercise when subjects were
on a low-sodium diet, ANP increased from 42 to
59 pg/mL, in contrast to a high-sodium diet
where the increase was from 72 to 119 pg/
mL. Thus, the increase in ANP with exercise
appears to be related to a number of factors:
stretch of the atrium due to volume changes, neurological inputs, and sodium intake.
rain Natriuretic Peptide
B
BNP, as its name implies, was first identified in
the brain and subsequently identified in other tissues, specifically in the heart [91, 92]. BNP is
collocated with ANP in the heart and appears to
have similar paths of regulation and actions. BNP
is not consistently altered in normal subjects in
response to acute exercise [41, 83, 93–95].
However, with long-duration exercise, such as a
100 km ultramarathon, BNP levels were increased
from resting values of 3.3–18.8 fmol/mL at the
end of the race. The response of BNP to exercise
is altered by a number of conditions [96]. When
subjects performed submaximal exercise on a
low-sodium diet, an increase in BNP was not
noted; however, on a high-sodium diet, a significant increase was seen. A similar finding was
reported with the presence or absence of fluid
217
intake in the course of exercise [83]. If subjects
did not ingest water, there was no response to
exercise, but if fluid was provided, BNP was
increased with exercise. In hypertensive subjects,
the increase in BNP with exercise was the same
with or without beta-blockade, in contrast to the
greater increase in ANP with beta-blockade [88].
This suggests that while similar mechanisms,
such as atrial stretch, fluid intake, and sodium
status, modify the response of both BNP and
ANP to exercise, the neurological component
present in the regulation of ANP is not an important factor for BNP.
Urodilatin
Urodilatin, a natriuretic hormone derived in the
kidneys, has been suggested to play a role in the
renal handling of sodium [97, 98]. Schmidt et al.
assessed the response of urodilatin and ANP during bicycle ergometer exercise at 60% of maximum for 1 h [99]. Plasma ANP concentrations
increased, and the excretion of urodilatin
decreased; i.e., the hormones had a negative correlation. The decrease in urodilatin was associated with a reduction in the percent of the filtered
sodium load excreted. As urodilatin increased,
the amount of sodium lost also increased. These
findings suggest a possible role in the regulation
of sodium homeostasis during exercise that needs
to be investigated further.
Adrenomedullin
Adrenomedullin is reported to have natriuretic
and diuretic effects. Adrenomedullin is produced
in the vascular endothelium and in smooth muscle cells. In humans, plasma concentrations are
responsive to changes in blood volume [100,
101]. Furthermore, changes in adrenomedullin
are correlated with changes in ANP and BNP in
patients. In normotensive subjects, adrenomedullin concentrations in response to submaximal
exercise of short duration were not altered, even
though ANP and BNP levels were increased. In
contrast, during maximal exercise, Tanaka and
colleagues found adrenomedullin to be increased
by 45% compared to at rest and to be negatively
associated with systolic blood pressure [102].
Piquard et al. also reported that with acute maximal
218
exercise, adrenomedullin increased from resting
levels of 15–29 pmol/L at the end of ­exercise
[103]. Yet others have found adrenomedullin to
be increased with submaximal exercise and
decreased with maximal exercise [104, 105].
Therefore, further investigation is warranted to
elucidate the responses and actions for adrenomedullin during exercise.
Fluid and Electrolyte Regulation
The management of fluids and electrolytes is a
careful balance between loss of salts and water
through sweat, shifts between body compartments, and conservation by the kidneys and
replenishment through ingestion [106]. While
some losses are tolerated during exercise, once
critical levels are exceeded, there are decrements
in performance. In order to avoid these reductions, a series of compensatory mechanisms are
activated that have to work in concert to maintain
the milieu, to optimize performance, and to avoid
subsequent morbidities and mortality.
Total Body Water
During exercise there is a loss of TBW, predominately via sweating and in part from increased
respiratory loss. The reduction of TBW is tolerated until a critical level is attained. The loss of
TBW during exercise is equivalent to the reduction in total body mass over the period of exercise
performance. Though this assumption has been
questioned, there is still a strong relationship
between the decrease in TBW and body mass
[107–109]. During long-duration exercise, the
reduction in TBW may exceed 5% of body mass.
In a 70 kg person, this would equate to fluid loss
of 3000–4000 mL [6, 8, 110]. In laboratory
experiments, a reduction of more than 2% body
mass has been shown to decrease performance
[110]. In contrast during competitive endurance
events, a reduction of greater than 4% body mass
was demonstrated to have a decrement in performance [9]. Of note, even with free access to
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water, a loss in TBW during exercise is observed.
This water loss, in the presence of fluids to ingest,
is referred to as voluntary dehydration [18, 111].
Voluntary dehydration represents about 20–30%
of the total loss of body water during an activity,
as 70–80% is replaced by supplemental intake
over the period of exercise. During a marathon
the average body mass loss was 2.3% even though
fluids were available. Interestingly, in subjects
finishing under 3 h, the loss was 3.1%, from 3 to
4 h 2.5%, and over 4 h 1.8% [112]. The ability to
tolerate a greater decrease in TBW was inversely
associated with finish time. These observations
suggest that individuals who are successful in
these events are able to tolerate a greater TBW
loss and still perform at a high level. The loss of
fluids sustained in the course of exercise is usually replaced in the subsequent 24 h [21, 29, 60,
113]. Irrespective of the TBW loss tolerance, at
some point the loss of TBW will impact the performance of an individual.
The loss of TBW during exercise is not equally
distributed throughout the body or between body
fluid compartments. Over the course of exercise,
there is a redistribution of fluids among the various compartments of the body, with a pronounced
reduction in plasma volume [59, 61, 65, 114]. The
reduction in plasma volume during maximal acute
exercise is 8–12%, resulting in a 5–7% decrease
in blood volume. This shift of fluids from the vascular space to the extravascular space has been
attributed in part to increases in endothelial permeability, which could possibly be modified
within specific tissues by angiotensin II, vasopressin, and norepinephrine [115–117]. The
decrease in blood volume is compensated for by
an increase in cardiac output and a redistribution
of blood flow [48, 49, 118, 119]. During the performance of exercise, the redistribution of fluids
within the vascular compartment is required to
meet the metabolic demands of active tissues and
to dissipate the thermal load resulting from the
increase in metabolism. This redistribution of
flow is the result of increases in local vascular
resistance, which is in part due to hormonal regulation, predominately by catecholamines, angiotensin II, and vasopressin.
13
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
Sweating
The principal means of fluid and electrolyte loss
during exercise is in sweat. Sweating is essential
to dissipate the increased thermal load incurred
by the elevation of metabolism with exercise
[120]. The density of sweat pores is highly variable among subjects, as is the magnitude of sweat
produced due to the subjects’ level of training
and prior adaptation and acclimation to a hot
environment [90, 120–123]. The rate of fluid loss
by sweating can be as high as 1500 mL/h [6, 18,
108, 124]. The magnitude of fluid loss in sweat is
hormonally mediated by vasopressin [125, 126].
Circulating levels of vasopressin are positively
associated with the rate and composition of sweat
during exercise. The rate of sweating during
exercise is coupled with the changes in plasma
osmolality and volume, the primary mediators of
vasopressin; thus, it has been difficult to separate
cause and effect [118, 119, 127, 128]. However,
local subcutaneous injection of vasopressin alters
the rate and composition of sweat from glands
exposed to an increase in local skin temperature
[129]. Plasma vasopressin concentrations have
been associated with sweat sodium concentration
and osmolality, suggesting vasopressin promotes
water conservation in the sweat gland [125, 130].
In addition, studies involving a possible role of
catecholamines on sweat rate have resulted in
conflicting findings [131, 132]. However, in a
study of the effect of fluid intake, it was shown
that the ingestion of a large volume, >3 L, was
associated with an increase in sweating, reduction in plasma concentration of norepinephrine,
and an increase in skin blood flow. In contrast,
the opposite effects were seen with ingestion of a
small volume, >0.5 L, during long-duration submaximal exercise in the heat. Therefore, an
increase in catecholamines appears to be associated with a decrease in skin blood flow that
results in a decrease in sweating.
Sweat is composed of a significant amount of
electrolytes [90, 120, 121, 133, 134]. Thus, during exercise the predominate means of the loss of
electrolytes is through sweat. The concentration
of sodium in sweat ranges from 20 to 135 mmol/L,
219
potassium from 3 to 35 mmol/L, and chloride
from 10 to 100 mmol/L, in contrast to “normal”
plasma concentrations (sodium 135–145 mmol/L,
potassium 3.5–5.0 mmol/L, and chloride
96–106 mmol/L) [135]. While the levels of electrolytes in sweat are lower than in plasma, the
losses are significant. At a sweat rate of 1.5 L/h at
a sodium concentration of 60 mmol/L, a total of
90 mmol would be lost or 3% of total body
sodium. As noted above, however, the concentrations of electrolytes in sweat are highly variable.
Electrolyte concentrations of sweat are decreased
as a result of training and heat acclimation [65,
90, 121]. The lower concentrations reduce the
tonicity of the sweat and therefore facilitate evaporation and cooling. In a comparison of 10 min of
acute maximal exercise to 60 min of submaximal
exercise (60% of maximum workload), minimal
differences in the electrolyte concentrations were
noted: sodium 70 vs. 77 mmol/L, potassium 7.7
vs. 4.8 mmol/L, and osmolality 171 vs. 172
mOSM/L for maximal and submaximal exercise,
respectively. The reductions in the sodium concentration of sweat appear to be in part mediated
by aldosterone [121, 136].
Fluid and Electrolyte Intake
Consumption is the primary means of replacing
the fluid and electrolytes losses incurred during
the course of exercise [18, 137, 138]. In the performance of long-duration exercise, 80% of the
fluid lost in sweat is replaced by voluntary ingestion if free access to fluids is provided [108,
137]. The extent to which volume losses are
replaced is dependent upon the composition of
the ingested fluid [137–141]. In humans during
extended exercise, the volume of fluid replacement appears to be closely regulated. In contrast,
the replacement of electrolytes does not appear
to be as closely titrated and is a by-product of
normal nutrient intake. Takamata et al. suggested
that 6–24 h after heavy exercise, salt appetite is
increased in association with a decrease in
plasma osmolality and sodium concentrations
resulting from fluid intake [113]. Leshem et al.
220
monitored salt intake after exercise and found a
voluntary increase of 50% in the amount of salt
added to food [142]. Passe et al. assessed the
acceptance of hypertonic saline fluids during
exercise and reported an increase in palatability
of a 60 mmol/lL sodium solution, suggesting a
relationship between sensory reception, hedonic
response, and drink composition in the replacement of electrolytes post exercise [143].
Replacement of electrolytes may be coupled
with hunger and increase in salt appetite. In animal models salt appetite is strongly associated
with angiotensin II; however, this proposed relationship has yet to be definitively demonstrated
in humans [11, 144, 145].
As previously noted, the replacement of fluids
is closely controlled over the course of exercise
and thus readily adjusted for following exercise.
This tight regulation is modulated by thirst, the
subjective sensation to seek and drink fluids
[144–147]. The subjective sensation of thirst can
persist for hours after exercise [113]. As described
earlier there is a level of voluntary dehydration
that can be tolerated in the performance of long-­
duration exercise, but the majority, about 80%, of
the fluid loss is replaced by drinking. The residual loss associated with the level of voluntary
dehydration is usually replaced within 24 h [21,
29, 113]. This process is associated with a variety
of factors, such as the increase in plasma osmolality and reduction in blood volume, both of
which are closely tied to the regulation of numerous hormones. Immediately after exercise
Takamata et al. found the subjective evaluation of
thirst to be immediately reduced upon ingestion
of fluids yet increased hours later in spite of
plasma osmolality being reduced [113]. This
increase in thirst was associated with an elevation
of aldosterone and presumably angiotensin II
[91, 147]. If the replacement fluid is water,
plasma osmolality and sodium concentration can
be decreased before blood volume loss is corrected, thus presenting conflicting regulatory
mechanisms resulting in a reduction in thirst
[148, 149]. Merry et al. reported the subjective
sensation of thirst to be associated with an
increase in osmolality during moderate exercise
C. E. Wade
under various levels of hydration in subject with
different levels of fitness (Fig. 13.2) [27].
Osmolality was also related to an increase in
vasopressin, suggesting a possible association
between vasopressin and thirst. Keneflick et al.
assessed the response of thirst during 1 h of walking at 50% of maximum on a treadmill in temperate (27 °C) or cold (4 °C) environments [150]. In
the cold environment, the sensation of thirst was
reduced by 40% and associated with lower levels
of vasopressin, even though plasma osmolality
was increased. The authors speculated that
peripheral vasoconstriction increased central
blood volume that was sensed as an actual
increase in blood volume. This hypothesis is supported in part by the observation that immersion
and dehydration, which increase and decrease
central blood volume, respectively, alter thirst via
volume-induced stimulation of the cardiopulmonary baroreceptors. Stimulation of these baroreceptors by an increase in volume results in
decreased vasopressin and PRA and increased
ANP [151]. In contrast dehydration causing a
reduction in volume elicits the opposite responses
[33]. The specific roles of these hormones in the
regulation of thirst during and following exercise
have yet to be clearly defined.
The ingestion of fluid during the performance
of exercise has been advocated to sustain performance [4, 6, 110]. To determine fluid replacement by water ingestion during exercise,
Robinson et al. had subjects perform two bouts
of exercise, one with and another without fluids,
on a cycle ergometer for 1 h at 85% of their maximum oxygen uptake [133]. The subjects
ingested 1.5 L of water to replace the fluid loss
due to sweating, which resulted in a 60%
decrease in the loss of body mass. The ingestion
of fluid did not alter sweat rate, the increase in
body temperature, or perceived exertion. Though
plasma osmolality and sodium concentrations
had a greater increase in the absence of water
intake, no differences in vasopressin or angiotensin II were reported. These findings were confirmed by McConell et al. who stated that
ingestion of fluids had little benefit on exercise
of 1 h [152]. However, others have consistently
13
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
shown hypohydration to impair performance.
There is an absence of data as to whether someone exercising should drink “as much as tolerable,” “to replace the weight lost during exercise,”
or “ad libitum”; thus, Noakes et al. had also
questioned the effects of fluid hydration during
exercise [153]. The role of hormones in this
debate is even more difficult to evaluate.
Rehydration is shown to attenuate the response
of atrial natriuretic hormone, vasopressin, and
PRA to exercise [24, 32, 66]. Furthermore, the
role of these hormones in the modulation of
thirst during exercise is confounded. At present
the data supports maintenance of an adequate
hydration status to avoid the adverse effects of
dehydration. The means of achieving this, and
the levels needed, have yet to be defined.
In light of the present state of data in this area,
an understanding of the function of hormones in
the regulation of thirst is essential. Hew-Butler
has reviewed the role of vasopressin in fluid balance and its possible role in dysnatremia, specifically exercise-associated hyponatremia [10].
Hyponatremia with exercise may result from
water retention associated with excess fluid
intake, sodium loss predominately via sweat, or
more likely a combination of these factors. Put
forth is the hypothesis that non-osmotic-­mediated
AVP release from the pituitary increases circulating levels of vasopressin leading to retention of
water, even if fluid intake does not exceed recommended guidelines. This inappropriate fluid
retention/overload could be a contributing factor
of hyponatremia and its subsequent sequelae.
The efforts from this group, in the lab and in the
field, provide insights as to the contribution of
vasopressin and other hormones to the regulation
of fluid and electrolyte homeostasis [10, 22, 26,
70, 71].
Renal Function
The action of hormones in the regulation of kidney function is well defined due to their role in
the pathophysiology of hypertension. While
extensive studies have been directed at the study
221
of hormones on kidney function during exercise,
the contribution of the kidneys to fluid and electrolyte balance is limited [59, 60, 154–157].
Zambraski described the limited contribution of
the kidney noting that in a normal individual, the
kidneys produce about 1 mL of urine a minute or
60 mL/h [53]. This is in comparison to the loss of
fluid from sweat on the order of 1000–1500 mL/h,
during moderate to heavy exercise. Zambraski
estimated that during exercise the renal conservation of water would only account for 4% of the
loss of water and about 8% for the sodium [53].
Thus, the conservation of fluid by the kidney is
hampered by the limited amounts of water and
electrolyte excreted in the basal state.
Nevertheless, the hormonal influences on the kidney provide insights into their role in the overall
maintenance of fluid and electrolyte homeostasis
during and following exercise [53, 60, 158].
enal Blood Flow
R
At rest the kidney receives about 20% or approximately 1000 mL/min of the overall cardiac output. During exercise renal blood flow is reduced
in relation to the intensity and duration of exercise. With mild to moderate exercise (50–70% of
maximum workload), there are negligible
changes, but with maximal exercise flow is
decreased by 40–60% from the normal [45, 48,
53, 158–160]. The reduction in renal blood flow
persists for over 1 h after completion of the exercise. This reduction is caused by vasoconstriction
of afferent arterioles, associated with an increase
in sympathetic nerve activity and circulating levels of norepinephrine derived from spillover from
the kidney [45, 47, 53, 159, 161]. In animal models upon initiation of exercise, there is an immediate reduction in renal blood flow which
increases over time to a steady state associated
with the level of exercise [162]. This immediate
decrease suggests the predominance of the neural
regulatory component in the initial phase of exercise. The reduction in renal blood flow decreases
the volume of fluid and electrolytes delivered to
the glomeruli of the kidney and in turn contributes to regional shifts in renal blood flow within
the kidneys.
222
lomerular Filtration Rate
G
The amount of fluid moving across the membrane of the glomeruli of the kidney is termed
the glomerular filtration rate. The movement of
fluid is the product of the drive pressure across
the membrane and oncotic pressure of the
plasma. As noted above there is an increase in
afferent arteriole resistance with exercise; however, this is accompanied by an increase in efferent arteriole resistance facilitating filtration. The
increase in efferent arteriole resistance is controlled by angiotensin II. Changes in the rate of
glomerular filtration are related to the intensity
and duration of exercise and may persist for up
to 24 h after exercise [163, 164]. Minimal
changes in filtration are observed with exercise
of less than 50% of maximum. With acute maximal exercise or long-­
duration exercise above
70% of maximum, the rate of filtration may be
decreased by 50–70%. With heavy exercise there
is also an increase in the permeability of the glomerular membrane as demonstrated by the
occurrence of an increase in protein excretion
[53, 165]. This alteration of permeability is suggested to be in part mediated by norepinephrine,
vasopressin, and angiotensin II and results in an
increase in the excretion of protein [53, 163,
166, 167].
rine Flow Rate
U
Urine flow rate is the product of the amount of
fluid filtered (glomerular filtration rate) and the
net reabsorption of fluid in the tubules. With
exercise of low intensity, there is either no change
or a slight increase in urine flow rate [39, 155].
With acute maximal exercise or long-duration
exercise eliciting voluntary dehydration, urine
flow rates are decreased by 20–60% of the normal basal levels of 0.8–1.2 mL/min [53, 59, 60].
This minimal decrease results in the conservation
of water in light of the losses due to sweating.
The decrease in the amount of filtered water is
predominately due to vasoconstriction of the
afferent arterioles caused by norepinephrine [45,
48, 131, 161]. Exercise also causes an increase in
the osmolality of urine, indicative of an increase
in the reabsorption of water [57–59]. However,
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decreases have been reported in urinary osmolality indicative of an increase in free water clearance during heavy exercise [53, 59]. Therefore
the role of vasopressin in the control of water
reabsorption in the collecting tubule during exercise has been questioned. There may be inhibition of vasopressin or the possibility of a
“washout” of the osmotic gradient in the medullary area of the kidney due to the redistribution of
blood flow associated with the actions of angiotensin II. After exercise the reduction in urine
flow persists and may contribute to the rectification of fluid loss along with increased drinking
[21, 113].
enal Handling of Electrolytes
R
At the normal rate of glomerular filtration, the
amount of fluid equivalent to the TBW is filtered
in 5–6 h. The filtrate contains electrolyte concentrations equivalent to those of plasma. Over the
course of traversing through the kidneys, 80–99%
of the filtered load of electrolytes is reabsorbed.
This reabsorption is hormonally mediated for
sodium and establishes an electrochemical gradient for the handling of other electrolytes and an
osmotic gradient for the handling of other solutes. With acute exercise, the decrease in the
excretion of electrolytes is predominately due to
the reduction in glomerular filtration rate [21,
113, 156]. During and following long-duration
exercise, the reabsorption of sodium is regulated
by aldosterone [21, 113]. With daily heavy exercise, there is a persistent increase in aldosterone,
which is strongly associated with an increase in
the reabsorption of sodium (Fig. 13.3) [21].
In summary, with exercise, kidney function
changes and is regulated by a number of hormonal systems. The major alterations effecting
fluid and electrolyte homeostasis are a decrease
in renal blood flow and an increase in the reabsorption of sodium. There are several fallacies as
to the contribution of these changes in kidney
function to the net maintenance of fluids and
electrolytes. The primary misunderstanding is
the quantitative contribution of the kidney to fluid
balance and the roles of hormones in these
changes.
13
Hormonal Regulation of Fluid and Electrolyte Homeostasis During Exercise
Summary
Exercise elicits increases in a number of hormones important in the regulation of fluid and
electrolyte homeostasis. The action of these hormones may persist for hours and days after completion of the exercise. While increases in
hormone levels are noted, the regulation and
actions of these hormones are often not well
defined, specifically in relation to the changes in
fluid and electrolyte balance during exercise.
There are issues as to the influence by the type
and duration of exercise on hormonal responses
that are not often accounted for. Recent efforts
employing multifactorial analysis are just beginning to define some of these factors. In addition,
the role of hormones in the etiology of the detrimental effects of exercise, such as dehydration
and dysnatremia, is beginning to be addressed.
Finally, evidence is mounting to show that exercise plays a vital role in fluid and electrolyte
homeostasis. Observations of the hormonal
responses to exercise will lead to a better understanding of both exercise physiology and related
disease processes.
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158–64.
Hormonal Regulation
of the Positive and Negative
Effects of Exercise on Bone
14
Whitney R.D. Duff and Philip D. Chilibeck
Introduction
Adequate levels of physical activity are important for bone health. Proper exercise training
increases bone mineral density and prevents
osteoporosis and fractures [1]. Too much exercise
without adequate energy replacement may however negatively affect hormone status (especially
reproductive hormones), and this may have a
negative impact on bone health. The intent of this
chapter is to cover this spectrum of effects of
exercise on bone physiology and health.
The “Negative Effects of Exercise on Hormonal
Regulation of Bone” section of this chapter covers
the negative effects of high levels of exercise,
especially without adequate dietary energy or calcium intake, on sex hormone (i.e., estrogen, testosterone) and calciotropic hormone (i.e., parathyroid
hormone, calcitonin, and vitamin D) levels and
how this can negatively impact bone health.
The “Positive Effects of Exercise on Hormonal
Regulation of Bone” section of this chapter covers how proper exercise training may be complimentary with sex hormones or may enhance
anabolic and calciotropic hormones to improve
bone health. Exercise may have additive or synergistic effects for increasing bone density when
combined with estrogen replacement therapy in
W. R.D. Duff · P. D. Chilibeck (*)
University of Saskatchewan, College of Kinesiology,
Saskatoon, SK, Canada
e-mail: phil.chilibeck@usask.ca
postmenopausal women. Although studies are
mixed, exercising may induce acute increases in
release of anabolic hormones (i.e., testosterone,
growth hormone, insulin-like growth factor-1) or
may alter release of calciotropic hormones (i.e.,
decrease parathyroid hormone, increase calcitonin and vitamin D). This may lead to changes in
basal levels of these hormones with chronic training and improvement in bone health.
egative Effects of Exercise
N
on Hormonal Regulation of Bone
egative Effects of Exercise
N
on Reproductive Hormone Status
Estrogen and Progesterone
Estrogen and progesterone are important sex hormones for maintenance of bone health in women.
Estrogen increases intestinal absorption of calcium [2] and decreases activity of bone-resorbing
cells (osteoclasts) [3], whereas progesterone may
positively affect cells involved in bone formation
(osteoblasts) [4]. Excessive exercise without adequate energy replacement may have a negative
impact on these hormones, resulting in amenorrhea, and negative impacts on bone health [5].
Athletic Amenorrhea Athletic amenorrhea
(i.e., cessation of menses in premenopausal
women) is most common in sports that require
lower body mass [2–4], including long-distance
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_14
229
230
running [5] and rowing [6], and activities that
involve subjective judgment [7], such as gymnastics [8], figure skating [9], and ballet [10].
Athletes in these sports may develop disordered
eating in an attempt to maintain the lower body
mass required. The “female athlete triad” was
proposed as a diagnosis when disordered eating
was present with amenorrhea and osteoporosis
[7, 11]. Now considered a spectrum ranging from
normal to varying degrees of pathology of the
three components, the female athlete triad can be
diagnosed when low energy availability (with or
without disordered eating) is present along with a
dysfunction in menstrual function and/or low
bone mineral density [7, 12]. The modifications
to the diagnoses guidelines increased overall
prevalence of the disorder, although total prevalence is still unknown [4, 7].
Amenorrheic athletes have lower bone density
than not only their eumenorrheic counterparts but
also sedentary controls and have a two- to fourfold higher stress fracture rate [13, 14]. For some
athletes however, high intensity of exercise, especially activities that involve high-impact forces or
high strains on bone due to muscle pull, may offset some of the negative effects of amenorrhea.
This may be the case in gymnasts [8, 15–17] and
rowers [6]. Amenorrheic dancers may [18] or
may not [10] have an elevated bone density at
weight-bearing sites, but have an increased incidence of stress fractures [19]. Longer durations
of menstrual dysfunction in dancers equate to
larger deficits in bone density at the spine [14, 20,
21], with scoliosis forming in some [19].
Amenorrheic runners or endurance athletes generally have decreased bone density, even at
weight-bearing sites [22–26], and this is associated with higher prevalence of stress fracture
[27–31]. Weight-bearing exercise may therefore
be of sufficient impact to be protective in gymnasts, but not in dancers and runners when normal menstruation is not maintained [26, 29].
Etiology of Athletic Amenorrhea Athletic
amenorrhea has been attributed to increased cortisol levels due to chronic exercise stress or an
imbalance between energy expenditure and
W. R.D. Duff and P. D. Chilibeck
energy intake (i.e., decreased energy availability), leading to reduced gonadotropin-releasing
hormone pulse generation at the hypothalamus,
subsequent decreased release of follicle-­
stimulating and luteinizing hormone from the
anterior pituitary during the follicular phase, and
reduction in the production of estrogen and progesterone in the luteal phase [2, 7]. Considering
those on the spectrum with less severe menstrual
dysfunction (i.e., not complete amenorrhea), a
blunted release of these hormones still occur due
to luteal phase defects [32]. The evidence for
both hypotheses has previously been outlined by
Loucks et al. [33] (see Chap. 11 in this book).
The “stress hormone” hypothesis is supported by
findings that high growth hormone levels and
hypercortisolemia are often reported in amenorrheic athletes indicating alterations in the
hypothalamic-­pituitary-adrenal axis [21, 34–39]
and centrally driven increases in corticotropin-­
releasing factors that negatively affect gonadotropin secretion in animals and humans [35, 36,
39–42].
The “low energy availability” hypothesis is
strongly supported by the literature. Firstly,
amenorrheic and eumenorrheic athletes have
lower dietary energy intakes relative to energy
expenditure [43, 44] and have endocrine profiles
(i.e., reduced levels of thyroid hormones;
Fig. 14.1) [43, 45, 46] that occur during chronic
energy deficiency [47]. Further, increased levels
of the starvation hormone adiponectin, signaling
“low energy availability” [39, 48], have been
found in gymnasts and ballet dancers [39, 49].
Leptin, with physiological levels proportional to
fat mass, could be considered the mediator hormone between energy availability and reproduction [50]. Low fat mass results in decreased
production of leptin and increased production of
ghrelin in amenorrheic athletes [2, 37, 39, 51–
55]; this suppresses the hypothalamic-pituitary-­
gonadal (HPG) axis leading to decreased estrogen
levels [2, 39, 56]. Finally, short-term induction of
menstrual cycle changes with exercise can be
prevented by adequate dietary compensation [33]
or administration of leptin [57]. “Low energy
availability” (i.e., negative energy balance) and
14
Hormonal Regulation of the Positive and Negative Effects of Exercise on Bone
a
2
Triiodothyronine levels (nmol/L)
b
Thyroxine levels (nmol/L)
100
*
1.6
80
1.2
60
0.8
40
0.4
20
0
EU
AM
ANX
231
0
*
EU
AM
ANX
Fig. 14.1 EU eumenorrheic athletes; AM amenorrheic
athletes; ANX anorexics. Amenorrheic athletes have endocrine profiles (i.e., decreased thyroid hormones) similar to
anorexics with chronic energy deficiency. (Data taken
from Refs. [43, 47]). ∗Eumenorrheic means are significantly different from amenorrheic and anorexic means
(p < 0.05)
the effect on the hypothalamus-pituitary-ovarian
axis are described in detail by Stafford et al. [2]
(summarized in Fig. 14.2). The decrease in bone
mineral density with athletic amenorrhea is
thought to be attributable to low energy availability affecting bone turnover, with resorption
favored over formation [50]. It is therefore suggested that athletes may be able to reverse menstrual disorders and prevent bone loss without
decreasing their energy expenditure (i.e., physical activity levels) by increasing their dietary
caloric intake [33]. This is supported by studies
where energy availability is decreased either by
energy restriction or by increased exercise. Low
energy availability induced by energy restriction
or increased exercise reduced leptin and insulin-­
like growth factor-1 (IGF-1) levels, but only
energy restriction decreased markers of bone formation [58].
studies showed estrogen therapy to induce an
overall statistically significant increase of 3.3%
at the lumbar spine site only [59]. Confounding
factors such as spontaneous resumption of menses and weight gain may influence the changes in
bone density versus estrogen per se. Estrogen
likely has no effect on metabolic factors that
impair bone formation, but rather controls bone
resorption, which may not necessarily be elevated in amenorrheic athletes [13, 60, 61]. As
such, amenorrheic dancers and runners who
resumed irregular menses and/or gained weight
had larger gains in spine bone density (6.3–17%)
over 15–24 months compared to those who
achieved neither [62–64]. Further, weight gain
was shown to independently predict bone density gains in oligo- and amenorrheic runners,
although dietary calcium intake did as well [65].
Considering that clinical findings of estrogen
therapy do not strongly support use for improving bone health in amenorrheic athletes [13, 50,
59], clinicians tend to recommend calcium and
vitamin D supplementation [66]; however, the
latter also has insufficient evidence in amenorrheic athletes, and there is no consensus
on appropriate dosage in this population [13].
Thus, the “cornerstone” of treatment has been
identified as improving energy availability by
increasing caloric intake while maintaining
energy expenditure, resulting in weight gain and
Prevention and Treatment of Athletic
Amenorrhea Previous pharmacologic strategies to improve bone health in hypothalamic
amenorrhea have included estrogen therapy and
calcium supplementation. Estrogen therapy has
shown mixed results, with some studies showing
improvements or maintenance of bone density
and with several others showing inconclusive
results [13]. A recent systematic review and
meta-analysis of controlled and noncontrolled
W. R.D. Duff and P. D. Chilibeck
232
Fig. 14.2 The
hypothalamic-pituitary-­
ovarian axis. Energy
imbalance causes
hypoestrogenism and
amenorrhea. Decreases
in leptin and increases in
ghrelin may influence
gonadotropin-releasing
hormone (GnRH)
secretion causing
subsequent decreases in
luteinizing hormone
(LH) and estrogen
production. (Adapted
from Stafford et al. [2])
Negative energy balance
Leptin
Ghrelin
Hypothalamus
Abnormal GnRH pulse
Anterior Pituitary
LH secretion
Ovaries
Estrogen
Bone
( resorption)
hopefully resumption of regular menses [7, 12,
13, 33, 50, 67, 68]. Despite improvements with
these treatments, bone density often still remains
lower than control levels in many formerly
amenorrheic athletes [2, 32, 62, 63, 69, 70]. This
suggests adolescent athletes with amenorrheainduced low bone mineral content may experience difficulty with “catch-up” accrual [22, 71]
and may develop premenopausal osteopenia and
be at higher risk of osteoporotic fractures later in
life [2, 13]. Even elite amenorrheic gymnasts
showed compromised skeletal health after retirement [72, 73]. Prevention of irreversible bone
loss due to reproductive, stress, and metabolic
hormone dysregulation as a result of energy deficiency is prioritized over treatment [39, 70, 74].
Treatment is difficult as athletes will be
resistant [46], but regardless should consider
multiple individualized factors [4], and utilize a
comprehensive assessment by a multidisciplinary team that includes a physician, dietitian,
and psychologist [2, 75, 76].
Testosterone
Excessive exercise without adequate energy
replacement may also affect sex hormone status
in men [77–80]. Adequate testosterone levels are
important for proper calcium absorption [81] and
stimulation of osteoblasts and therefore bone formation [82]. Reduced concentrations of free and
total testosterone in response to chronic endurance exercise have been deemed the “exercise-­
hypogonadal male condition” [79]. More
recently, a parallel to the female athlete triad has
been suggested in males engaged in sports that
emphasize leanness or weight control, with the
triad including low energy availability (with or
without disordered eating), hypogonadotropic
14
Hormonal Regulation of the Positive and Negative Effects of Exercise on Bone
hypogonadism, and low bone mineral density
[83]. Disruption in the hypothalamic-pituitary-­
testicular axis with excessive exercise in males
[79] may have similar etiology as dysregulations
seen in females, owing to decreased energy availability [78] or production of stress hormones
[84–87]. It is suggested however that the HPG
axis may be less sensitive to physical stress and
more sensitive to disordered eating in males [88].
A few studies, but not all, have successfully
linked low energy availability to the suppression
of the HPG axis in men [31, 89–91]. Previous
evidence supports this link, such that a shift in
caloric balance following a season in wrestlers
allowed for an increase in body weight, returning
testosterone levels to normal [78]. However, the
available research on this topic in men is
extremely limited compared to that which has
studied women.
Simple measures of hormone levels, such as
testosterone, that influence reproduction have
been relied upon to determine hypogonadotropic
hypogonadism in males, since clinical determination would require complicated techniques
such as sperm and fertility analyses, rather than
simply a lack of menses to determine the female
alternative of amenorrhea [83]. Cross-sectional
studies have shown testosterone levels are lower
in endurance- and resistance-trained men compared to controls [77, 78, 89, 90, 92–96], while
studies also demonstrate testosterone suppression after periods of high volume training [97–
103]. Notably, some studies showed a lack of
elevation of luteinizing hormone corresponding
to suppressed testosterone [77, 93, 103] which
may be attributed to deficiency of gonadotropin-­
releasing hormone, as seen in female athletes
[104, 105]. Further, male athletes who participate
in low- or no-impact and weight-class sports are
at higher risk of impaired bone health, although a
representative prevalence remains unknown [83].
These observations may imply a connection
between training, suppressed testosterone, and
impaired bone health. This is evident in a couple
of studies where reduced testosterone in male
cyclists [106] or runners [31], attributable to low
energy availability, was associated with lower
lumbar spine bone mineral density or increased
233
fractures. However, the association between testosterone levels and bone health is less clear in
other studies. Some studies show that while male
runners [88, 107–111] and cyclists [112–114]
have reduced bone mass, primarily at the lumbar
spine, testosterone levels are normal [88, 107,
110, 112]. To add to these observations in runners, in one study a negative association between
training volume and bone density with no difference in testosterone levels was shown [110],
while another study showed a negative association between training volume and testosterone
levels with bone density unaffected [115]. One
useful study that assessed testosterone, luteinizing hormone, and bone density demonstrated that
after 5 months of training, triathletes (classified
as endurance athletes) had higher bone density
despite lower testosterone levels without elevated
luteinizing hormone than controls [103]. Finally,
a very recent study noted that resistance-trained
runners had higher bone density at all sites than
nonresistance-trained runners and controls, with
no differences in testosterone or any bone biomarkers except vitamin D (which was higher);
these authors concluded the benefits for bone
were therefore attributable to chronic loading of
the bone and not physiologically modulated by
low testosterone [104].
Reduced levels of androgens in males have
rarely been linked to corresponding reductions in
bone mass, possibly because testosterone levels
remain within the normal range, albeit usually at
the extreme low end (unlike estrogen in females,
which fall below the normal range) [61, 79, 88].
In one case study, a male with hypogonadism,
reduced bone mass, and skeletal fragility had testosterone levels return to normal after treatment
with clomiphene citrate which stimulates gonadotropin secretion [116]. In a 4-year exercise intervention in middle-aged men, Remes et al. [117]
reported significant associations between estradiol and testosterone and bone turnover markers
at baseline, although only associations between
estradiol and bone formation were significant at
the 1-year and post-intervention mark. More
recently it was shown that estradiol levels in male
athletes, rather than testosterone, predicted bone
mineral density, although, notably, testosterone
234
predicted estradiol levels [88]. Further research is
needed to confirm which factors of the triad
affects the hypothalamic-pituitary-testicular axis
the greatest. Such research should focus on alterations in estrogens rather than androgens in
males [83] and include metabolic hormones
leptin and ghrelin [79].
egative Effect of Exercise
N
on Calciotropic Hormones
The calciotropic hormones (parathyroid hormone, calcitonin, and to an extent,
1,25-­dihydroxyvitamin D3 [vitamin D]) are
involved in calcium homeostasis and bone
metabolism [118]. Parathyroid hormone is
released from the parathyroid gland in response
to low blood calcium levels. Parathyroid hormone stimulates osteoclasts to resorb bone so
that blood calcium levels can be restored [119].
Calcitonin has a less powerful but opposite effect.
Calcitonin is released from the thyroid gland
when blood calcium levels are high and inhibits
bone resorption. Vitamin D stimulates active
intestinal calcium absorption. High levels of
exercise may alter secretion of these calciotropic
hormones, negatively affecting bone mineral
status.
egative Effects of Exercise
N
on Parathyroid Hormone
Although parathyroid hormone is mainly recognized for its role in bone resorption, it has also
been known to have a role in bone formation
[120]. Whether parathyroid hormone has catabolic or anabolic effects depends on the mode of
administration (when given as a pharmaceutical),
signaling mechanism, and duration of exposure
[121, 122], with continuous infusion stimulating
bone resorption and intermittent exposure stimulating bone formation [123, 124]. Exercise is
another important mediator of parathyroid hormone that is dependent on exercise duration and
intensity [123]. Thus, studies of the effect of
exercise on parathyroid hormone and bone
responses are mixed. The studies demonstrating
negative or no effects are discussed below, with
W. R.D. Duff and P. D. Chilibeck
studies demonstrating positive effects discussed
later in the chapter.
A study in mice utilizing an acute exercise
bout (30-minute running) led to a twofold
increase in systemic parathyroid hormone [125].
The response of parathyroid hormone to acute
exercise bouts in humans is quite variable with
studies reporting an increase in release [121,
126–132], a decrease in release [133], and no
change [134–136]. One study in particular compared acute bouts performed at 15% above or
below ventilatory threshold; parathyroid hormone was only increased after the higher intensity bout, suggesting a stimulation threshold
[137]. Thus, intensity as well as duration, type of
exercise, and recovery may influence parathyroid
response, accounting for the discrepancies
between studies [123]. Acute bouts of higher-­
intensity exercise are thus likely to increase
release, and in this case, parathyroid may promote an anabolic effect on bone by increasing
osteoblast response to mechanical loading [118,
128, 132, 138]. In response to an exhaustive acute
exercise session, there were no differences
between trained endurance athletes and recreationally active athletes, with both groups showing a postexercise increase in parathyroid
hormone, as well as markers of bone turnover;
thus, training status does not appear to influence
the response to acute exercise [121, 139]. Aside
from exercise variables, parathyroid response to
acute exercise bouts can also be affected by calcium concentrations, acidosis, catecholamines,
and training [123]. Acute exercise bouts cause
decreases in serum ionized calcium concentrations, possibly through dermal losses via sweating or increased urinary calcium [140]. This
acute decrease in ionized calcium may stimulate
release of parathyroid hormone and an increase
in bone resorption [140]. This implies acute
release of parathyroid hormone is deleterious, in
contrast to the studies mentioned above.
Consuming calcium before exercise sessions, or
injection of calcium during exercise sessions,
may attenuate this effect [140, 141].
Two short-term (6–8 weeks) training studies
have shown no changes in parathyroid hormone,
with no substantial changes in bone resorption
14
Hormonal Regulation of the Positive and Negative Effects of Exercise on Bone
235
[142, 143]. However, the response of bone formation was different between these studies, with
the study in young women showing increases
[143] and the study in older men showing
decreases [142]. These differences could be
attributed to the population study (age, sex), as
well as the training type. One longitudinal study
also showed no changes in parathyroid hormone
or bone resorption after a 7-month triathlon season, with increases in bone formation and subsequent gains in lumbar spine bone density [144].
On the other hand, excessive chronic high-­
intensity exercise training may cause an increase
in the continuous release of parathyroid hormone
[126] and a deleterious effect on bone. This may
be related to increases in stress hormones, such
as catecholamines. Parathyroid hormone release
is stimulated by catecholamines in animal models [145]; this correlates with the intensity [146]
or volume [126] of exercise. Two longitudinal
exercise training studies indicated elevated basal
levels of parathyroid hormone, which were associated with increased bone turnover and reduced
bone mineral [147, 148]. This effect is not consistent however, as further training resulted in a
decrease in parathyroid hormone and an increase
in bone mineral [148], and in another study,
training resulted in elevated parathyroid hormone levels and an increase in bone mineral
[149]. There may be an interaction between different hormone systems that affect the set point
at which parathyroid hormone is released, with a
decrease in estrogen (as seen with chronic overtraining) resulting in increased parathyroid hormone release [134]. Low estrogen levels in
young overtrained athletes may amplify the
effects of parathyroid hormone on bone turnover, similar to what is seen in postmenopausal
women [150].
release [134]. This may avert the beneficial effect
of calcitonin on preventing bone resorption in the
subset of runners with low bone mass.
Studies assessing vitamin D levels in athletes
demonstrate that concentrations vary greatly
[151] and can be influenced by the time of year
and sunlight exposure, as well as diet and other
lifestyle choices [152]. Vitamin D levels may be
lower in runners with low bone mass (i.e., amenorrheic athletes) in comparison to eumenorrheic
athletes and controls [27], although levels were
still within a normal range. Male cyclists (i.e.,
non-weight bearing) have also been shown to
have low bone density coincident with low vitamin D status [106, 112, 153]; this may be related
to low energy availability [106]. The majority of
recent studies show that athletes are deficient or
insufficient in vitamin D, with deficiencies tending to exist in winter months; therefore, effect of
season may have a greater influence on vitamin
D status that is compounded by excessive exercise with inadequate dietary intake [154–162].
Similar to what occurs in hypoestrogenism, the
stimulus of loading the bone may override the
negative effect of vitamin D deficiency [151].
Indeed, a large cross-sectional study examined
male athletes of differing sports, ages, and ethnicities and found no association between bone
density and vitamin D deficiency [163], and a
study in female synchronized swimmers showed
that although vitamin D and insulin-like growth
factor-1 (IGF-­1) levels were suppressed, bone
ultrasound measurements and markers of bone
turnover were not different compared to controls [164].
egative Effects of Exercise
N
on Calcitonin and Vitamin D
Excessive levels of exercise may negatively
impact calcitonin and vitamin D levels. Female
runners with low bone mass had decreased calcitonin release in response to elevated blood calcium levels following exercise, whereas runners
with normal bone mass had increased calcitonin
I nteractions Between Exercise
and Estrogen for Increasing Bone
Mass
ositive Effects of Exercise
P
on Hormonal Regulation of Bone
Exercise and estrogen replacement may be complimentary therapies for increasing bone mass in
postmenopausal women. When the two are
­combined, their effects on some bone sites may
236
be synergistic (i.e., greater than the addition of
each therapy alone). Animal studies have demonstrated either additive [165] or synergistic
[166, 167] effects with the two therapies in postmenopausal models. The majority of studies in
postmenopausal women have shown exercise
and estrogen replacement therapy to have an
additive [168, 169] or synergistic [170] effect on
bone mass of the spine and a synergistic effect
on whole-body bone mass [168, 170]. One study
found a synergistic effect on bone density at all
sites measured (hip, spine, and total body) [171].
Another study found individual benefits on bone
density at the spine, but no synergistic effects
[172]. However, a recent meta-analysis showed
hormone replacement therapy in combination
with exercise training had greater benefits for
bone density at the femoral neck and lumbar
spine than exercise alone, seemingly confirming
a synergistic effect [173]. Despite this, women
have become hesitant to utilize hormone replacement therapy for bone health due to safety concerns [174]; thus, interest in phytoestrogens as
alternative therapy has grown. Animal studies
using postmenopausal models have shown cooperative effects of exercise and isoflavone (a
plant-­based phytoestrogen) on bone density and
properties at the hip, lumbar spine, and total
body [175–177]. However, a recent study in
postmenopausal women contradicted animal
study findings, showing that either therapy alone
maintained bone density of the total hip, but
when the therapies were combined, there was a
negative interaction that resulted in a decrease at
the same site [178]. The differences between
animal and human studies may reflect the signaling mechanism, with lower doses in humans
activating primarily estrogen receptor-β which
downregulates the detection of exercise loads,
while higher doses in animals also activate estrogen receptor-α which increases proliferation of
osteoblasts in response to loads [178]. Thus, this
implies that estrogen may augment the response
of bone to loading (or vice versa) with exercise
and estrogen synergistically increasing bone
mass when estrogen receptor-α is preferentially
activated [179].
W. R.D. Duff and P. D. Chilibeck
ffects of Exercise on Anabolic
E
Hormones
Anabolic hormones, such as testosterone, growth
hormone, and IGF-1 increase following acute
exercise sessions, and basal levels of these hormones may also increase in response to chronic
training. Synthesis of IGF-1 may be in conjunction
with growth hormone, as its synthesis in the liver
or other sites, such as muscle or bone, may be
mediated by growth hormone [180]. Each of these
anabolic hormones activates osteoblasts and therefore stimulates bone formation [82, 181, 182].
This section covers the effects of acute and chronic
exercise on release of anabolic hormones and their
potential for positively affecting the bone.
cute Effects of Exercise on Anabolic
A
Hormones and Bone Metabolism
Acute exercise sessions may stimulate increases
in blood levels of anabolic hormones in both men
and women. In men, a single bout of exercise has
been shown to result in increases in growth hormone [183–186], IGF-1 [186, 187], and testosterone levels [80, 183, 184, 188, 189]. In women,
growth hormone [190–192], IGF-1 [193], and
testosterone [191, 194] levels also increased in
response to acute exercise. Thus, similar
responses to acute exercise occur in women, particularly regarding growth hormone [195–197],
although the response seems to be attenuated
with aging in both sexes [185, 198, 199]. The latter is likely due to insufficient exercise stimulus
in older adults [200]. The exercise-induced
response of growth hormone is well recognized
and may be due to neural input, lactate, or nitric
oxide, with pulsatile release amplified when
“threshold” is attained [195]. It is presumed that
hepatic secretion of IGF-1 is stimulated by the
elevations in growth hormone [196]. However,
increased production of IGF-1 has not always
followed the same pattern as growth hormone
changes [186, 187, 191, 192]; therefore, their
release may be independent. The adrenal cortex
releases testosterone, and this may be the mechanism by which testosterone levels in females are
increased with exercise [194].
14
Hormonal Regulation of the Positive and Negative Effects of Exercise on Bone
Several studies have related the increases in
anabolic hormones with acute exercise to changes
in markers of bone turnover. Repeated one-leg,
knee-extension exercise resulted in an increase in
serum growth hormone, with an exercise-induced
uptake of growth hormone over the thigh and a
release of IGF-1, in men and women with a
simultaneous increase in markers of bone turnover [135]. A 30-minute cycling session in
trained males increased serum growth hormone
and IGF-1 [201], while biomarkers of bone turnover also increased [202]. Finally, high-force
eccentric contractions in males induced increases
in IGF-1 and makers of bone turnover [203]. This
release of anabolic hormones and increase of
bone turnover may result in increased bone formation with training, which may translate to
enhanced bone mineral with long-term training.
ffects of Exercise Training on Anabolic
E
Hormones and Bone Mass
A high bone mass in some athletic groups may be
associated with high basal levels of anabolic hormones. For example, young women involved with
resistance training [204] or gymnastics training
[205] have higher bone mass along with higher
levels of IGF-1 compared to aerobically trained
women and sedentary controls. In aerobically
trained females, testosterone levels are significantly associated with bone density [206].
Endurance-trained postmenopausal women have
higher bone density, IGF-1 levels, and a trend
toward higher growth hormone levels than sedentary controls [207]. Alternatively, amenorrheic
adolescent endurance athletes have lower bone
mass and lower levels of IGF-1 levels than sedentary controls, with IGF-1 levels acting as an independent predictor of apparent lumbar bone density
[25]. These cross-sectional studies suggest that
exercise training may enhance basal anabolic hormone levels and stimulate bone formation. For
premenopausal women, this may hold true as long
as regular menses are maintained. Higher bone
mass in athletes, however, is not always associated with increased anabolic hormone levels.
Male masters athletes involved in speed-power
events had greater bone mineral density than
237
endurance athletes and controls, but with no differences in testosterone or IGF-1 levels [208].
Also, male runners who participated in resistance
training had higher bone mineral density than runners not participating in resistance training, but
with no differences in testosterone [104].
Longitudinal training studies relating increases
in anabolic hormones to increases in bone mineral
density are mixed in their findings. Following a
7-month triathlon season, male triathletes had significant gains in lumbar spine bone density, with
corresponding increases in IGF-1, although testosterone levels did not change [144]. Six months
of aquatic exercise in postmenopausal women
increased IGF-1 and growth hormone levels,
along with enhancements in bone properties of
the calcaneus, as assessed by ultrasound [209].
Twelve months of resistance or jump training in
middle-aged men with low bone mass increased
lumbar spine bone mineral density, bone formation markers (relative to resorption markers), and
IGF-1 levels [210]. Other studies in humans
assessing changes in anabolic hormones and bone
health have demonstrated that beneficial effects of
training on bone can be realized without changes
in anabolic hormones. Eight weeks of resistance
training in older men and women reduced markers of bone resorption without changes in IGF-1
levels [211]. Sixteen to 24 weeks of resistance
training of middle-­aged or older men increased
femoral neck or lumbar spine bone mineral density without changes in levels of testosterone,
growth hormone, and IGF-1 [212, 213]. Likewise,
gymnastics training produced significant increases
in lumbar spine bone mineral density in young
women [214] and calcaneus mechanical competence in pre- and peri-pubertal males [215] without a change in serum IGF-1 levels.
ositive Effects of Exercise
P
on Calciotropic Hormones
Parathyroid Hormone
Parathyroid hormone stimulates bone resorption
to maintain homeostasis when blood calcium
levels are low [119] although several studies
238
have shown the parathyroid response is independent of calcium [127, 146, 216, 217]. With
chronic exercise training, parathyroid hormone
levels may be lowered [130, 207, 209]. This has
been associated with higher bone mineral values: In cross-­sectional studies, male and female
endurance-trained athletes have been found to
have lower serum parathyroid hormone levels
associated with higher bone mineral density
when compared to inactive controls [130, 207].
Six months of aquatic exercise training in postmenopausal women reduced parathyroid hormone levels while enhancing bone structural
properties at the calcaneus [209]. Rats
endurance-­
trained by treadmill exercise also
have lower parathyroid hormone levels and
higher bone mass compared to untrained rats
[218]. It is suggested that endurance training
induces a new set point of parathyroid hormone
release regulated by calcium, or permanently
suppresses its release [118], since corresponding higher calcium concentrations were found
with low parathyroid levels [130, 207]. More
recently, mice were put through a short-term
(21 days) training program, while parathyroid
hormone was inhibited or increased. Parathyroid
inhibition attenuated the structural-level
mechanical property increases seen in placebotreated mice, while parathyroid enhancement
increased trabecular and cortical bone volume
with no effect on tissue- and structural-­
level
mechanical properties as seen in placebo-treated
mice [125] .
In contrast to the above studies, an increase
in basal levels of parathyroid hormone has been
found following a resistance training program
that increased bone mineral density in postmenopausal women [149]. As mentioned in the
“Negative Effects of Exercise on Parathyroid
Hormone” section, parathyroid hormone may
have anabolic effects on bone through stimulation of osteoblasts, if released in an intermittent
fashion [124]. Further research is needed to
determine the exact direction of changes in
basal parathyroid hormone levels in response to
different training protocols and whether these
changes can be considered beneficial or detrimental to bone.
W. R.D. Duff and P. D. Chilibeck
alcitonin and Vitamin D
C
Few studies have looked at the effects of exercise
on calcitonin levels. In response to an acute exercise bout, calcitonin levels have been shown to
increase [133]. Limited studies have determined
the effects of exercise training, and those that did
have shown inconsistent results. Short-term exercise training was shown to have no effect on
serum calcitonin levels in one study [207], while
other studies showed increased calcitonin levels
[209, 219, 220]; this could prevent bone
resorption.
Cross-sectional studies indicate that vitamin
D levels may be elevated in endurance-trained
[207] and resistance-trained [104, 221] individuals, as well as decathletes [222, 223]. This is
associated with a higher bone mass in some of
these individuals compared to inactive controls
[104, 207, 221, 222]. Rats trained by treadmill
exercise have an increase in vitamin D levels,
increased calcium balance, increased intestinal
calcium absorption efficiency, and increased
bone mass compared to untrained rats [218, 224].
Increases in growth hormone release with exercise training [135, 207] may simulate the production of the active form of vitamin D [225],
resulting in increased intestinal calcium absorption [223] and increased bone mass [118]. Male
triathletes showed increased vitamin D levels
after a 7-month season, with gains in lumbar
spine bone density [144]. While growth hormone
was not measured in this study, IGF-1 increased
post-season; this may also affect vitamin D
production.
Directions for Future Research
Extreme exercise training negatively impacts
bone owing to increased stress and changes in
metabolic hormones (i.e., increased cortisol and
ghrelin, reduced leptin), eventually suppressing
the HPG axis and decreasing estrogen (in
females) or testosterone (in males) production.
This suppression manifests as athletic amenorrhea, in conjunction with the female athlete
triad, in premenopausal women and has been
researched a great deal. However, research on
14
Hormonal Regulation of the Positive and Negative Effects of Exercise on Bone
h­ypogonadotropic hypogonadism and the athletic triad in males is still lacking. Such future
research in male athletes should focus on alterations in estrogens [83] and metabolic hormones
[79] and include longitudinal follow-ups to determine if males also experience difficulty in “catchup” accrual of bone mineral. Further, longer-term
studies determining the efficacy of treatment
plans for the athletic triad that incorporate individualized factors and are delivered by a multidisciplinary team should be studied [2, 4, 75, 76].
Such treatment plans should focus on determining if improving energy availability can prevent
reductions in reproductive hormones that may
occur with chronic exercise.
Research has consistently shown that acute
exercise results in an increased anabolic hormone response in both men and women with
corresponding changes in bone turnover.
Further, cross-sectional data shows athletes
have high basal anabolic hormone levels and
bone mass. However, more research is required
to understand the effects of exercise training on
anabolic hormones and bone density. Such
research should focus on the development of
exercise prescriptions for optimal enhancement
of long-term hormone profiles that result in
bone formation.
Evidence regarding vitamin D in relation to
bone in athletes is quite consistent. Research on
the other calciotropic hormones, calcitonin and
parathyroid hormone, is lacking or inconsistent.
Studies determining the effects of acute exercise
and exercise training on calcitonin levels and
bone are needed. Further research is needed to
determine the response of parathyroid hormone
to different training protocols and whether these
changes can be considered beneficial or detrimental to bone.
Summary
Chronic exercise training without adequate
energy replacement induces release of stress
and metabolic hormones, which in turn suppress
the hypothalamic-pituitary-gonadal axis and
downregulate production of reproductive
239
hormones. These hormonal changes ultimately
lead to low bone mineral density, which presents with low energy availability and a dysfunction in menstrual function (females) or
hypogonadotropic hypogonadism (males) in the
athletic triad [83]. In some cases, particularly in
gymnasts, overloading the bone negates the deleterious effects of hypoestrogenism. Regardless,
prevention strategies in males and premenopausal females should focus on early identification of those at risk of developing the athletic
triad. Prevention is particularly pertinent
because evidence suggests bone loss experienced in previously amenorrheic athletes is irreversible. If it is too late for prevention, the
“cornerstone” of treatment is improving energy
availability. Postmenopausal women can counteract deleterious effects of hypoestrogenism
via hormone replacement therapy and exercise
training, which has a synergistic effect for bone
density at clinically relevant sites (i.e., femoral
neck and lumbar spine).
Athletes tend to be deficient in the calciotropic hormone vitamin D, particularly in winter
months, with this effect compounded by low
energy availability. However, the stimulus of
bone loading may again override the negative
effects of the deficiency. The effect of exercise
on other calciotropic hormones (e.g., parathyroid hormone) is highly dependent on exercise
variables. Due to a stimulation threshold, acute
bouts of high-intensity exercise increase release
of parathyroid hormone that results in an anabolic effect on bone, if calcium levels are adequate prior to exercise. Alternatively, chronic
exercise training may decrease parathyroid hormone levels, which has been associated with
higher bone mineral values. However, the set
point at which parathyroid hormone is released
is altered with changing estrogen levels and calcium concentrations.
Anabolic hormones (i.e., testosterone,
growth hormone, and IGF-1) increase in
response to acute bouts of exercise in both men
and women, although the response is attenuated
with age likely due to insufficient exercise stimulus (see Chap. 23 in this book). Trained individuals have high basal levels of anabolic
240
hormones that may be associated with high bone
mass, suggesting the changes in bone t­urnover
with acute exercise may translate to improved
bone health with long-term training.
W. R.D. Duff and P. D. Chilibeck
13. Ducher G, Turner AI, Kukuljan S, Pantano KJ,
Carlson JL, Williams NI, et al. Obstacles in
the optimization of bone health outcomes in
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2011;41(7):587–607.
14. Pearce G, Bass S, Young N, et al. Does weight-­
bearing exercise protect against the effects of
exercise-induced oligomenorrhea on bone density?
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Interrelations Between Acute
and Chronic Exercise Stress
and the Immune and Endocrine
Systems
15
Jonathan Peake
Introduction
Interaction between the endocrine and immune
system is necessary to regulate our health. However,
under some conditions, stress hormones can overstimulate or suppress the immune system, resulting
in harmful consequences [1]. Stress is often considered negative, yet it is an intrinsic part of everyday
life. Stress is not clearly defined; it is context-specific and depends on the nature of factors that challenge our body. Internal stimuli will elicit different
stress reactions compared with external stimuli [1].
Similarly, some stressors will induce responses that
may benefit survival, whereas others will cause disturbances that may endanger our health. Stress also
depends on how our bodies perceive and respond to
stressful stimuli [1].
Several important factors determine whether
stress hormones stimulate or inhibit the immune
system. These factors include [1]:
• The effects of stress on the distribution of
immune cells in the body
• The duration of stress
• Hormone concentrations
• The timing of stress hormone exposure relative
to the activation status of immune cells (i.e.,
naїve vs. activated, early vs. late activation)
J. Peake (*)
School of Biomedical Sciences, Queensland
University of Technology, Brisbane, QLD, Australia
e-mail: jonathan.peake@qut.edu.au
Exercise is a reproducible and quantifiable
model of stress and is useful for studying the
interactions between the endocrine and immune
systems. Exercise stimulates the secretion of a
variety of stress hormones, but catecholamines,
cortisol and growth hormone are most closely
linked with exercise-induced changes in immune
function. Research on the interactions between
endocrine and immune systems following acute
exercise and chronic training is important.
Regular exposure to mild short-term stress can
potentially enhance immune function and lead to
various health benefits. Conversely, prolonged
exposure to the chronic stress of intense training
may inhibit certain immune functions that are
required for health maintenance. This chapter
describes the regulatory roles of stress hormones
on immune cell counts and activity during acute
exercise and following chronic exercise training.
Figure 15.1 summarises the immunoendocrine
interactions during exercise and their potential
functional significance.
echanisms of Interaction: In Vitro
M
Evidence
Stress hormones modulate immune function
directly by binding to cognate receptors on
immune cells and indirectly by modulating the
production of cytokines (e.g., IFN-γ, IL-1β, IL-6,
TNF-α) [2]. Glucocorticoid receptors are
© Springer Nature Switzerland AG 2020
A. C. Hackney, N. W. Constantini (eds.), Endocrinology of Physical Activity and Sport,
Contemporary Endocrinology, https://doi.org/10.1007/978-3-030-33376-8_15
249
J. Peake
250
Brain
Exercise
Sympathetic
nerve fibre
Heart
Neuroendocrine
Skin
HPA axis
Lung mucosa
Adrenal
gland
↑ Cardiac output
↑ Shear stress
Demargination from
vascular pools
-Spleen?
-Lung?
-Liver?
-Active muscles?
Peripheral
circulation
ACTH
Gut
Medulla
Cortex
Catecholamines
Cortisol
Cell trafficking
-Adhesion molecules
-Apoptosis
Other immune
mediators
-Cytokines
-Chemokines
-Heat shock proteins
Preferential mobilisation
of cells with altered
effector phenotype?
Effector functions
-Microbial killing
-Cytokine expression
Tissue
migration/
homing
Fig. 15.1 Potential mechanisms by which stress hormone interacts with the immune system during exercise. (Modified
from TOM-Systemdruck GmbH, Walsh et al. [170])
expressed on monocytes and B lymphocytes,
whereas glucocorticoid receptor expression is
much lower on CD3+ T cells and neutrophils [3, 4].
β2-adrenoreceptors for catecholamines are
expressed on (in descending order) natural killer
(NK) cells, monocytes, B lymphocytes and T suppressor lymphocytes [5]. Macrophages [6] and
neutrophils [7] also express β2-­adrenoreceptors.
Within T lymphocyte subpopulations, β2adrenoreceptors are mainly expressed in naїve
CD4+ T cells and T helper 1 and T helper 2 cells
[8–10]. mRNA for α-adrenoreceptors is expressed
by activated T cells [11] and in peripheral blood
mononuclear cells of patients with juvenile rheumatoid arthritis but not healthy individuals [12].
Although B lymphocytes, monocytes and neutrophils all express growth hormone receptors
[13–15], growth hormone most likely exerts its
effects on the immune system by binding to prolactin receptors, which are expressed on monocytes and B and T cells [16]. Immune cells also
express receptors for other stress hormones,
including substance P [17], neuropeptide Y [18],
corticotrophin-releasing hormone [19] and serotonin [20].
Glucocorticoids regulate the activity of immune
cells by binding to glucocorticoid receptors, which
in turn suppresses the transcription factors activator protein 1 (AP-1) and nuclear factor κ B (NFκB)
[21]. Glucocorticoids inhibit AP-1 transcriptional
activity by preventing the oncoproteins c-Fos and
c-Jun from binding to the AP-1 consensus binding
site in DNA [22]. Glucocorticoids inhibit NFκB
transcriptional activity through two mechanisms.
15
Interrelations Between Acute and Chronic Exercise Stress and the Immune and Endocrine Systems
Firstly, glucocorticoids can induce expression of
the inhibitory protein IκB, which then prevents
NFκB from translocating to the nucleus where it
initiates transcription [23]. Secondly, physical
interaction or cross-talk between glucocorticoid
receptors and NFκB can suppress transcription
[24, 25]. By suppressing the transcriptional activity of AP-1 and NFκB, glucocorticoids regulate
various immune functions, including cytokine
production [21]. In particular, glucocorticoids
inhibit monocyte production of type 1 cytokines
IL-12 and IFN-γ, which in turn favours the production of type 2 cytokines IL-4 and IL-10 by
CD4+ lymphocytes and peripheral blood mononuclear cells [26–29]. Type 1 cytokines regulate
the activity T cytotoxic cells, NK cells and macrophages which defend against intracellular pathogens. Type 2 cytokines regulate the activity of B
lymphocytes, eosinophils and mast cells, which
defend against extracellular pathogens [30]. The
type 1/type 2 cytokine balance determines the balance between cell-mediated vs. humoral immunity and the risk of various immune-related
disorders [31]. For information on the effects of
glucocorticoids on other aspects of immune function, readers are referred to other more comprehensive reviews [21, 32].
Binding
of
catecholamines
to
β2-­
adrenoreceptors can inhibit IL-2 and IFN-γ and
stimulate IL-4 and IL-10 production by T cells
and peripheral blood mononuclear cells [26, 33,
34]. Similar to glucocorticoids, catecholamines
can therefore induce a shift towards type 2 cytokine production. The combined effects of glucocorticoids and catecholamines on IFN-γ, IL-4 and
IL-10 production by peripheral blood mononuclear cells are in fact additive [26]. However, there
are some inconsistencies in the literature concerning the effects of β-agonists on cytokine production. Some studies report that T helper 2
lymphocytes do not respond to β-agonist stimulation [9, 35], but more recent data indicate that
activated T cells do produce cytokines following
β-agonist stimulation [10]. The effects of
β-agonists on cytokine production may also be
dose-dependent. Low concentrations of β-agonists
(i.e., 1–10 nM) stimulate cytokine production,
whereas high concentrations (i.e., 100 nM to
251
10 μM) inhibit cytokine production by T cells
[10]. Downstream from cyclic AMP, β-agonists
inhibit cytokine production by T cells by blocking
the calcium-/calmodulin-dependent protein phosphatase calcineurin and p38 mitogen-­
activated
protein kinase, but not NFκB [10, 36]. For information on the effects of catecholamines on other
aspects of immune function, readers are referred
to other more comprehensive reviews [21, 31, 37].
In comparison with glucocorticoids and catecholamines, less is known about the effects of
growth hormone and prolactin on the immune
system. The actions of growth hormone and
insulin-­like growth factor-1 (IGF-1) do not overlap entirely, but growth hormone exerts many of
its actions through IGF-1. Neither growth hormone nor IGF-1 is essential for immune function,
but growth hormone influences various aspects of
immune cell development and activity [38].
Growth hormone inhibits apoptosis of CD4+ T
cells following treatment with dexamethasone
[39]. Growth hormone, through binding to its
receptor on the surface of T cells, may activate
phosphatidylinositol 3 kinase (which regulates
cell proliferation) and NFκB (which controls
apoptosis through the anti-apoptosis protein
Bcl2) [40]. IGF-1 also stimulates macrophages to
produce reactive oxygen species [41] and
increases NK cell activity [42]. Prolactin is also
not essential to normal immune function [38], but
it can promote lymphocyte proliferation [43] and
haematopoiesis [44].
Interactions between the neuroendocrine and
immune systems are bidirectional. Pro-­
inflammatory cytokines released from immune
cells (e.g., IL-1β, IL-6 and TNF-α) mediate communication between the immune system and the
central nervous system. Cytokines can alter activity of the central nervous system through
humoral, neural and cellular pathways [45].
Cytokines can pass the blood–brain barrier
directly [46]. Alternatively, immune cells can
pass across the blood–brain barrier and release
cytokines into the central nervous system [47].
Cells comprising the blood–brain barrier also
secrete various cytokines [48]. Cytokines may
signal the central nervous system by stimulating
afferent nerves, although this concept remains
J. Peake
252
somewhat controversial [49]. One theory proposes that cytokines target the blood–brain barrier during systemic inflammation, whereas they
target afferent nerves during localised inflammation [49]. Cytokines can pass back across the
blood–brain barrier into the circulation following
intracerebroventricular injection of lipopolysaccharide (LPS) [50]. Cytokines interact with components of the central nervous system, resulting
in behavioural changes. Specifically, cytokines
alter neurotransmitter function, neuroendocrine
activity, neural plasticity and neural circuitry.
These actions can induce fever, changes in appetite, fatigue and depression [45].
tress Hormones and Leukocyte
S
Mobilisation In Vivo
A number of studies have investigated the effects
of stress hormones on circulating leukocyte numbers by infusing variable doses of stress hormones in healthy humans over 30 min up to 5 h.
Cortisol raises the number of circulating neutrophils, whereas it suppresses the number of lymphocytes, and does not alter the number of Leu+
NK cells [51, 52]. By contrast, adrenaline
increases the number of circulating total lymphocytes and NK cells [51, 53–55]. The number of
circulating monocytes also rises 1–2 h following
infusion of adrenaline [53, 55, 56].
In contrast with NK cells, the effects of adrenaline and the β-agonist isoproterenol on circulating
T lymphocyte subpopulations are somewhat variable. In response to these agents, the number/percentage of circulating CD4+ T helper cells decreases
[54, 56, 57] or increases [53, 58], whereas the number/percentage of circulating CD8+ T cytotoxic
cells increases [53, 54, 58], decreases [57] or
remains unchanged [56, 59]. The number/percentage of circulating B lymphocytes decreases [53] or
remains unchanged following infusion of adrenaline or isoproterenol [54, 56, 59]. More recent
research indicates that adrenaline increases the
number of circulating CCR7−CD45RA+CD8+
effector T cells, CD4−CD8− γ/δ T cells,
CD3+CD56+ NK T-like cells, CD16+CD56dim cytotoxic NK cells and CD14dimCD16+ pro-inflamma-
tory monocytes. These cells most likely originate
from marginated pools on the endothelial surface
of blood vessels [60]. In addition to these findings,
γ/δ T cells and T cells expressing chemokine receptors (CXCR2, CXCR3 and CCR5) are mobilised
into the circulation following psychological stress.
These responses correlate with cardiac activation
[61, 62].
The effects of noradrenaline on circulating
leukocytes are also variable. One study has
reported that noradrenaline raised the number of
circulating neutrophils, monocyte, lymphocytes
and CD16+ NK cells [58, 63]. Another study
found no changes in the numbers of these cell
types or T lymphocyte subpopulations following
treatment with noradrenaline [54]. These inconsistent findings may be due to differences
between these studies in noradrenaline dose and
in the duration of hormone infusion and blood
sampling times relative to the period of infusion.
Combined treatment with cortisol and adrenaline increases the number of circulating neutrophils for up to 12 h [52]. Growth hormone
infusion in humans (2 IU) increases neutrophil
number, but does not alter blood mononuclear
cell subpopulations [64].
tress Hormones and Leukocyte
S
Function In Vivo
Several of the studies described above have also
examined changes in immune cell function following infusion of stress hormones in healthy
humans. Cortisol does not alter Leu+ NK cell
activity [51] or neutrophil chemotaxis or
­production of reactive oxygen species [65]. By
contrast, adrenaline increases the activity of
CD16+ NK cells [53, 55]. Similarly, noradrenaline
infusion in humans (16 μg/min for 1 h) also
increases CD16+ NK cell activity [63]. The effects
of catecholamines and isoproterenol on lymphocyte proliferation vary. Isoproterenol reduces
lymphocyte proliferation [54], whereas adrenaline and noradrenaline have no effect [54, 57].
This disparity may be due to variable changes in
lymphocyte subpopulations in response to these
agents. Adrenaline increases the number of T
15
Interrelations Between Acute and Chronic Exercise Stress and the Immune and Endocrine Systems
cells that express IFN-γ, IL-2, IL-4 and TNF-α
[53]. Adrenaline and noradrenaline infusions also
raise the plasma concentrations of IL-6 and IL-1
receptor antagonist (IL-1ra) under normal resting
conditions [66–68]. In contrast, adrenaline infusion prior to experimental endotoxemia reduces
subsequent changes in the plasma concentrations
of IL-6, IL-8 and TNF-α [69]. Hydrocortisone
treatment immediately prior to experimental
endotoxemia does not alter subsequent changes in
plasma IL-6 concentration but attenuates plasma
TNF-α concentration and increases plasma IL-10
concentration endotoxemia [70, 71]. Conversely,
IL-6 and IFN-γ increase the plasma concentrations of cortisol and ACTH cortisol [72, 73], while
infusion of LPS increases the plasma concentrations of adrenaline and cortisol [59].
To summarise, glucocorticoids, catecholamines and growth hormone bind to specific
receptors on the surface of immune cells. This
hormone-receptor binding mediates leukocyte
trafficking and functional activity. In vitro, glucocorticoids and catecholamines induce a shift in
the balance of type 1/type 2 cytokines towards
greater production of type 2 cytokines. Growth
hormone regulates immune cell activity through
IGF-1 and can inhibit apoptosis of T lymphocytes. In vivo, cortisol mobilises neutrophils but
reduces the number of circulating lymphocytes
and does not alter circulating natural killer cell
numbers. Catecholamines increase the total number of circulating lymphocytes, monocytes and
natural killer cells. They also stimulate natural
killer cell activity. By contrast, the effects of catecholamines on circulating lymphocyte subpopulations and lymphocyte activity are more variable.
By crossing the blood–brain barrier, immune
cells and cytokines can alter the function of the
central nervous system.
Immunoendocrine Responses
to Acute Exercise
Exercise immunologists have used various
approaches to investigate the interaction between
the endocrine and immune systems during exercise. On a basic level, some research has assessed
253
the correlation between changes in stress hormones and immunological variables following
exercise. Other research has examined the interactions between the endocrine and immune systems by using different exercise workloads,
carbohydrate and caffeine supplementation, thermal stress or drugs. A small number of studies
have also investigated how exercise-induced
immune changes alter the activity of the central
nervous system.
orrelations Between Stress
C
Hormones and Immunological
Variables
McCarthy et al. [74] first provided evidence that
following brief, intense exercise, the number of
circulating lymphocytes correlated positively
with the plasma concentrations of adrenaline
(ρ = 0.67, p < 0.05) and noradrenaline (ρ = 0.68,
p < 0.05). Plasma adrenaline concentration also
correlates positively with the number of circulating neutrophils after short, intense exercise [74,
75] and endurance exercise [76]. Rhind et al.
investigated the relationships between stress hormones and immune cells following exercise.
Stepwise multiple linear regression indicated that
plasma adrenaline concentration accounted for
some of the variation in CD3+ T cells, CD4+ T
helper cells, CD8+ T cytotoxic cells and CD3−/
CD16+/CD56+ NK cells [77]. Plasma noradrenaline concentration also explained some of the
variation in CD3−/CD16+/CD56+ NK cells and
CD19+ B cells [77]. Steensberg et al. [78]
­discovered that following 2.5 h running at 75%
VO2max (maximal oxygen uptake), the number of
T helper 2 cells that produce IL-2 and IFN-γ
decreases below pre-exercise values, and this
response is inversely correlated with plasma
adrenaline concentration. Brenner et al. [79] used
stepwise multiple linear regression to examine
stress hormones and immune cells following cold
exposure. Plasma noradrenaline concentration
accounted for some of the variation in CD3+ T
cells, CD8+ T cytotoxic cells and CD19+ B cells,
whereas plasma adrenaline concentration was
only linked with changes in CD19+ B cells [79].
254
The relationship between plasma cortisol concentration and the number of circulating immune
cells is more variable. Some studies report no
relationship [74, 80] or an inverse relationship
[81] between plasma cortisol concentration and
the number of circulating neutrophils after exercise. Other studies suggest that cortisol does
mediate neutrophil mobilisation following exercise [76, 77, 82, 83]. The association between
plasma cortisol concentration and the number of
circulating monocytes following exercise is also
inconsistent [77, 81]. It does seem, however, that
plasma cortisol concentration accounts for some
of the variation in CD4+ T helper cells and CD19+
B cells following exercise [77]. These inconsistent findings may be due to variation in blood
sampling points used to examine the association
between plasma cortisol concentration and the
number of circulating immune cells. In contrast
with adrenaline, cortisol mobilises neutrophils
into the circulation in a more delayed and prolonged fashion [51, 52]. Recent evidence indicates that plasma cortisol concentration correlates
strongly with lymphocyte apoptosis after resistance exercise [84]. Although growth hormone
can mobilise neutrophils at rest [64], there is no
clear evidence to indicate that growth hormone
regulates the number of circulating neutrophils
following exercise [81].
Several studies suggest that stress hormones
also regulate cytokine responses to exercise. The
plasma concentrations of adrenaline, noradrenaline, cortisol and growth hormone correlate with
the plasma concentrations of IL-6, IL-1ra, IL-12
and TNF-α following exercise in both thermoneutral and hot conditions [85–87]. The plasma
concentrations of noradrenaline and cortisol also
correlate with plasma IL-6 concentration following cold exposure [79, 88]. It is unclear whether
hormones or cytokines are the driving factor
behind these relationships. Stress hormones and
cytokines regulate body temperature during exercise, albeit through distinct mechanisms [89].
Adrenaline may stimulate a small rise in plasma
IL-6 concentration during exercise [68].
Alternatively, the correlation between plasma
adrenaline and IL-6 concentrations following
exercise may be purely coincidental, because
J. Peake
both adrenaline and IL-6 regulate muscle glycogen depletion during exercise [90, 91]. IL-6
release from skeletal muscle during exercise correlates with arterial IL-6 concentration [92].
Treatment with the glucocorticoids hydrocortisone and dexamethasone reduces plasma IL-6
concentration during exercise [85]. However,
IL-6 stimulates cortisol release at rest [72].
Further research is required to clarify the interactions between IL-6 and cortisol during exercise.
xercise Workload, Stress Hormones
E
and Immunological Variables
Stress hormones are released into the circulation
as the intensity of exercise increases. Plasma
adrenaline, noradrenaline and growth hormone
concentrations rise in an exponential manner
with increasing intensity [93–95]. By contrast,
plasma cortisol concentration only increases
above exercise intensities of >60% VO2max [76,
96, 97]. Based on these hormone responses, a
number of studies have compared immunological
responses to exercise of variable intensity and
duration.
Foster et al. [93] first provided evidence that
catecholamines influence leukocyte mobilisation
as a function of exercise intensity. The number of
circulating granulocytes and lymphocytes
increased with workload. Using the β-antagonist
propranolol, they demonstrated that during exercise, catecholamines regulate changes in lymphocytes, but not granulocytes [93]. Compared
with moderate-intensity exercise, the number of
circulating monocytes is similar, while CD4+ T
helper cells, CD8+ T cytotoxic cells and T cell
proliferation decrease below pre-exercise values
after high-intensity exercise [82, 97, 98].
Conversely, the number of CD19+ B cells is
higher after high- vs. moderate-intensity exercise
[82]. The number of circulating NK cells and NK
cell activity is similar immediately after moderate- and high-intensity exercise, while NK cells
and activity decrease below pre-exercise values
2 h after high-intensity exercise [98]. These studies did not evaluate the relationship between
stress hormones and these intensity-dependent
15
Interrelations Between Acute and Chronic Exercise Stress and the Immune and Endocrine Systems
immune changes. However, it seems likely that
stress hormones play a more dominant role in
mediating immune changes during high-intensity
exercise. The plasma concentrations of IL-6,
IL-1ra and IL-10 are also higher following highvs. moderate-intensity exercise [76, 92, 99, 100].
As discussed above, adrenaline may stimulate a
minor rise in plasma IL-6 and IL-1ra concentration during exercise [66, 68], but it is more likely
that IL-6 stimulates IL-1ra and IL-10 late in exercise [72].
Carbohydrate Supplementation,
Stress Hormones and Immunological
Variables
Cortisol and adrenaline play key roles in mediating metabolism during exercise [90, 101]. Many
studies have used carbohydrate supplementation
to manipulate stress hormone responses and
examine the mechanisms of exercise-induced
changes in immune cell counts and activity.
With the exception of a few studies [102–104],
carbohydrate consumption during endurance
exercise generally reduces the plasma concentrations of adrenaline, cortisol and growth hormone
[105–112]. This decrease in the release of stress
hormones most likely accounts for the decline in
the number of circulating neutrophils and monocytes following carbohydrate ingestion during
exercise [102, 103, 107, 109–111, 113]. By contrast, although carbohydrate supplementation
attenuates plasma cortisol concentration, in general, it does not prevent the post-exercise decline
in the number of circulating lymphocytes, lymphocyte subsets or NK cells [110, 114–118].
The effects of carbohydrate supplementation
on other exercise-induced changes in immune
cell function are variable. Despite changes in
stress hormones, not all studies demonstrate that
carbohydrate consumption maintains or increases
neutrophil and monocyte function [102, 103,
107, 109, 113, 119]. Most research indicates that
carbohydrate supplementation does not prevent
the post-exercise decrease in lymphocyte proliferation [114, 118, 120]. However, Lancaster et al.
[115] found that consuming carbohydrate reduces
255
plasma cortisol concentration and helps to maintain the number of IFN-γ+ CD4+ and CD8+ T cells
and IFN-γ production by these cells during exercise. The metabolic stress of low muscle glycogen appears to increase plasma cortisol
concentration and the number of circulating leukocytes, but does not alter lymphocyte proliferation during exercise [121, 122]. Carbohydrate
supplementation increases IL-2- and IFN-γ-­
stimulated NK cell activity, but not IL-4- and
IL-12-stimulated NK cell activity [116, 117].
These effects on NK cell activity are independent
of changes in plasma cortisol concentration [116,
117]. Nieman et al. [123] discovered that carbohydrate ingestion during exercise reduced plasma
cortisol concentration but did not alter salivary
immunoglobulin A concentration (when adjusted
for saliva protein concentration and secretion
rate). However, changes in salivary immunoglobulin A concentration were negatively correlated
with plasma cortisol concentration, and this relationship predicted the incidence of upper respiratory illness in the 2 weeks after exercise [123].
With a few exceptions [103, 106, 112], most
research shows that carbohydrate attenuates the
rise in plasma concentrations of IL-6, IL-10 and
IL-1ra (but not IL-8 or TNF-α) following exercise
[105, 108–111]. These cytokine responses to consuming carbohydrate during exercise may be
partly linked to changes in catecholamine release.
Carbohydrate supplementation does not influence
leukocyte mRNA expression of IL-6, IL-8, IL-10
and IL-1ra or monocyte intracellular production
of IL-6 and TNF-α following exercise [105, 106].
Carbohydrate ingestion attenuates the release of
IL-6 from the skeletal muscle during exercise, but
the effects of carbohydrate on mRNA expression
of IL-6 and IL-8 in the skeletal muscle following
exercise are variable [110, 111, 124, 125].
affeine Supplementation, Stress
C
Hormones and Immunological
Variables
Although caffeine is a well-known stimulant of
the central nervous system, only a small number
of studies have focused on its effects on stress
J. Peake
256
hormones and immune responses to exercise.
Ingesting 6 mg caffeine 1 h before endurance
exercise consistently raises plasma adrenaline
concentration [126–130]. Compared with a placebo treatment, caffeine supplementation does
not alter the number of circulating neutrophils
following exercise or neutrophil production of
reactive oxygen species [129, 130]. The number
of circulating CD3−/CD56+ NK cells is greater
compared with a placebo treatment, whereas
changes in the number of activated NK cells
expressing CD69 are variable after exercise and
caffeine ingestion [131, 132]. Changes in the
total number of circulating lymphocytes after
exercise and caffeine intake are also variable
[129, 130]. The numbers of circulating CD4+ T
helper cells and CD8+ T cytotoxic cells are lower,
while the numbers of these cells that express the
activation marker CD69 are greater after exercise
and caffeine intake compared with a placebo
treatment [126]. Caffeine supplementation also
increases the concentration and secretion rate of
salivary immunoglobulin A and the plasma concentration of heat shock protein 72 after exercise
compared with a placebo treatment [127, 128].
This variation in the effects of caffeine on
exercise-­induced immune changes may be due to
differences in exercise protocol, blood sampling
times and the habitual caffeine intake of the study
participants.
hermal Stress, Stress Hormones
T
and Immunological Variables
Some researchers have compared changes in
stress hormones and immunological variables
following exercise in hot vs. cold/thermoneutral
conditions. Several studies have examined
responses to exercise in hot vs. cold water. This
approach appears to be more effective than comparing responses to exercise in hot vs. cold/thermoneutral ambient conditions, because water is a
more effective conductor of heat than air. For
detailed discussion on the effects of thermal
stress on the endocrine and immune systems,
interested readers should consult the comprehensive review by Walsh and Whitham [89].
Plasma stress hormone concentrations are
higher following exercise in hot vs. cold water,
and these responses most likely account for the
higher numbers of circulating neutrophils and
lymphocytes following exercise in hot water [77,
81, 133–135]. However, not all research supports
a link between stress hormones and the number
of circulating leukocytes following exercise in
hot conditions [136, 137]. This relationship may
vary depending on the demands of exercise.
Within the lymphocyte subsets, CD3+ T cells,
CD34+ T helper cells, CD8+ T cytotoxic cells and
CD3−/CD16+/CD56+ NK cells (but not CD19+ B
cells) are higher at the end of exercise in hot vs.
cold/thermoneutral conditions [77, 122]. By contrast, the number of circulating CD3+ T cells is
lower 2 h after exercise in hot vs. thermoneutral
conditions [122].
The effects of thermal stress on neutrophil
function following exercise are also variable,
with reports of an increase [138], a decrease
[137] or no change [122, 134]. Thermal stress
during exercise increases lymphocyte proliferation per cell (despite higher plasma cortisol concentration) [122], whereas it does not alter NK
cell activity per cell [122, 139]. The plasma concentrations of IL-10, IL-1ra, IL-12 and TNF-α
are consistently higher after exercise in hot vs.
cold/thermoneutral conditions, whereas changes
in the plasma concentrations of IL-6, IL-8 and
granulocyte-colony-stimulating factor (G-CSF)
are less consistent [86, 134, 136–138].
rugs, Stress Hormones
D
and Immunological Variables
Several studies have used drugs to manipulate
stress hormone responses to exercise and examine the resultant immunological responses. The
findings of these studies are equivocal, possibly
because of variation in the exercise protocols,
treatment periods and drugs used in these
studies.
As described previously, Foster et al. [93]
treated men with a single dose of the non-­
selective β1-/β2-antagonist propranolol 10 min
before incremental exercise. They discovered
15
Interrelations Between Acute and Chronic Exercise Stress and the Immune and Endocrine Systems
that during exercise, propranolol reduced the rise
in the number of circulating lymphocytes, but not
neutrophils or plasma catecholamine concentrations. This finding suggests that catecholamines
may not regulate leukocyte mobilisation directly
during incremental exercise. Instead, catecholamines may work indirectly by increasing blood
flow, which strips leukocytes from the endothelial surface of blood vessels in marginal pools
such as the lungs. Murray et al. [140] conducted
a follow-up study in which they treated men and
women with propranolol or the selective β1-­
antagonist metoprolol for 1 week prior to an
incremental exercise test. Neither drug reduced
post-exercise plasma catecholamine concentrations compared with the control trial. However,
compared with the control trial, propranolol (but
not metoprolol) reduced the total number of circulating lymphocytes, numbers of CD4+ T helper
cells and CD8+ T cytotoxic cells and NK cell
numbers and activity and reduced the post-­
exercise decline in lymphocyte proliferation
[140]. These findings suggest that circulating catecholamines may not mobilise lymphocytes into
the circulation. Instead, these cells may be mobilised from the spleen in response to direct activation of β1-/β2-adrenergic receptors in the spleen
[141].
Starkie et al. [142] treated men with the selective α1-antagonist prazosin and the non-selective
β-antagonist timolol or placebo 2 h prior to
20 min cycling at ∼78% VO2max. Plasma catecholamine concentrations were higher, whereas
plasma cortisol concentration was lower after
exercise in the drug trial compared with the placebo trial. Starkie et al. [142] attributed the
greater catecholamine response in the drug trial
to reduced clearance of catecholamines by
β-receptors. The numbers of circulating lymphocytes and monocytes increased during exercise in
both trials but were lower immediately after exercise in the drug trial compared with the placebo
trial—despite the higher plasma catecholamine
concentrations. This finding conflicts with other
research showing that infusion of adrenaline or
isoproterenol raises the number of circulating
lymphocytes [51, 53, 54]. One possible explanation for this difference is that the drugs used in
257
the study by Starkie et al. [142] may target different adrenergic receptors on lymphocyte compared with adrenaline or isoproterenol. The
numbers of circulating IFN-γ+ CD3+ T cells,
IL-2+ CD3+ T cells and IFN-γ+ CD3−/CD56+ NK
cells increased during exercise in both trials.
However, the numbers of these cells were lower
after exercise in the drug trial compared with the
placebo trial. IL-2 production by CD3+ T cells
and IFN-γ production by both IFN-γ+ CD3+ T
cells and IFN-γ+ CD3−/CD56+ NK cells
decreased during exercise similarly in both trials.
These findings suggest that α- and/or β-adrenergic
receptor stimulation does not regulate cytokine
production by T cells and NK cells during
exercise.
Mazzeo et al. [143] treated women with prazosin or placebo for 3 days before cycling for
50 min at 50% VO2max. Prazosin reduced plasma
IL-6 concentration after exercise compared with
the placebo. Papanicolaou et al. [85] treated men
with hydrocortisone, dexamethasone or a placebo
4 h before 25 min running at 78% VO2max. Both
hydrocortisone and dexamethasone attenuated
plasma IL-6 concentration after exercise compared with the placebo.
vidence for Interactions Between
E
the Central Nervous and Immune
Systems
As outlined above, considerable attention has
focused on how stress hormones regulate immune
responses to exercise. The immune system is also
capable of altering the function of the central nervous system. Several studies have examined this
issue, and it is likely that more research will be
conducted in this area in the future. In mice,
exercise-­induced muscle damage stimulates macrophages residing in the brain to secrete IL-1β
into the surrounding tissue [144, 145]. This
response appears to increase perceptions of
fatigue, reduce voluntary activity and delay
recovery from exercise [146]. In humans,
Steensberg et al. [147] observed that at rest, the
concentrations of IL-6 and the cellular chaperone
heat shock protein 72 (HSP72) are two to three
258
times higher in cerebrospinal fluid compared
with plasma. Although exercise stimulates the
systemic release of IL-6 and heat shock protein
72, their concentrations remain stable in cerebral
spinal fluid, which indicates that they do not
cross the blood–brain barrier [147]. The brain
releases small amounts of IL-6 into the systemic
circulation during exercise, and this is independent of hyperthermia [148]. The functional significance of this response is not certain. It may
provide a signal to the liver to increase glucose
output, or it may be a more general indication of
increased neural activity during exercise [148].
hronic Interactions Between
C
the Endocrine and Immune Systems
Compared with the amount of research on acute
exercise, fewer studies have examined interactions between stress hormones and immunological variables following chronic training. Most
studies have simply documented the effects of
intensified training on simultaneous changes in
stress hormones and immune cell counts at rest
and/or in response to acute exercise. Very few
studies have specifically examined the relationship between changes in stress hormones and
immune cell counts and function.
Several studies report no changes in resting
plasma and urinary cortisol concentrations,
immune cell counts or serum cytokine concentrations after intensified training [149–153].
Robson-Ansley et al. [154] discovered no
changes in resting plasma cortisol or the number
of circulating neutrophil counts but did find that
resting plasma IL-6 concentration was persistently elevated following 4 weeks of intense
training. Fry et al. [155] observed that resting
plasma cortisol concentration decreased, while
the numbers of circulating neutrophils, monocytes and lymphocytes did not change after
10 days of intense interval training. The number
of circulating CD3+, CD4+ and CD8+ T cells and
CD20+ B cells also remained unchanged, whereas
the number of circulating CD56+ NK cells
decreased and CD25+ T cells increased following
10 days of training [155]. It is unlikely, however,
J. Peake
that these changes in CD56+ NK cells and CD25+
T cells were related to changes in plasma cortisol
concentration. Smith and Myburgh [156] reported
no change in resting plasma cortisol concentration but found that CD4+ and CD8+ T cell counts
and CD16+/CD56+ NK cells decreased following
4 weeks of intense training. Makras et al. [157]
observed an increase in urinary cortisol concentration, an increase in CD4+ T cell count and a
decrease in neutrophil count at rest after 4 weeks
of military training. Ortega et al. [158] found that
neutrophil phagocytic activity was higher in
female athletes compared with non-athletes. In
the athletes, neutrophil phagocytic activity correlated positively with plasma cortisol concentration, whereas it correlated negatively with plasma
ACTH concentration. Findings from the study by
Cunniffe et al. [159] suggest that elevated salivary cortisol concentration with training may
reduce salivary immunoglobulin A concentration, resulting in increased susceptibility to upper
respiratory illness. Some of the variability among
these studies may result from differences in the
physical fitness of study participants, training
loads and blood sampling times.
The effects of chronic training on cortisol and
immune responses to acute exercise are also
­variable. Verde et al. [160] reported that changes
in serum cortisol concentration, CD3+ T cell
counts and lymphocyte proliferation after acute
exercise were all attenuated following 3 weeks of
intense training. Lancaster et al. [161] discovered
that 2 weeks of intense training reduced plasma
cortisol concentration but did not alter lymphocyte production of the type 1 cytokine IFN-γ or
the type 2 cytokine IL-4. In contrast with these
findings, other research indicates no effect of
chronic training on exercise-induced changes in
plasma and salivary cortisol concentration,
immune cell counts or salivary immunoglobulin
A concentration [150, 152, 162].
A small number of studies have examined
changes in plasma or urinary catecholamine concentrations and immune cell counts following
chronic training. Imrich et al. [150] found no
changes in plasma catecholamine concentration
or immune cell counts at rest or in response to
acute exercise following 6 weeks of training.
15
Interrelations Between Acute and Chronic Exercise Stress and the Immune and Endocrine Systems
Hooper et al. [163] reported that both the number
of circulating neutrophils and plasma noradrenaline concentration were elevated in swimmers
showing symptoms of overtraining compared
with swimmers who were not overtrained after
6 months of training. However, it is unclear
whether these responses were linked in any way.
Mackinnon et al. [151] observed that urinary norepinephrine concentration decreased, whereas
plasma noradrenaline and leukocyte counts at
rest did not change following 4 weeks of intense
training. Makras et al. [157] found that the ratio
of adrenaline to noradrenaline in urine increased
after 4 weeks of military training. This response
correlated positively with CD4+ T cell counts and
correlated negatively with neutrophil counts.
Biological Significance
of Interactions Between
the Endocrine and Immune Systems
Dhabhar [1] proposes the following analogy to
explain the possible significance of acute stress
on the immune system. Within minutes of the
onset of stress, catecholamines stimulate the
body’s ‘soldiers’ (i.e., leukocytes) to leave their
‘barracks’ (i.e., spleen, lung, bone marrow, lymph
nodes) and enter the ‘boulevards’ (i.e., blood vessels and lymphatics). As stress proceeds, glucocorticoids are released which stimulate leukocytes
to exit the bloodstream and enter potential ‘battle
stations’ (i.e., skin, lung, gastrointestinal and
urinary-­
genital tracts, mucosal surfaces and
lymph nodes) in preparation for immune challenges that may occur in response to stressful
stimuli [1].
In the context of exercise, the factors that
stimulate the release of stress hormones are most
often non-harmful. These factors may include
demands for (1) increased blood flow to contracting muscle (to deliver oxygen and nutrients) and
skin (for thermoregulation) and (2) release of
energy substrates from the liver and adipose tissue (e.g., glucose, fatty acids, amino acids) to
support muscle metabolism. Interaction between
the endocrine and immune systems during exercise can therefore be considered as rather non-­
259
specific. However, stress hormones may (incidentally) prime immune cells to respond to
infectious pathogens and/or airborne pollutants
that invade mucosal surfaces lining the respiratory tract.
Dhabhar [1] proposed that the effects of stress
on the immune system and general health depend
on the duration of exposure to stress. Acute and
intense stress may enhance immune function, and
mild stress of moderate duration may promote
immunosurveillance, while chronic stress
may cause immune dysregulation [1].
Immunoprotection resulting from acute stress
may lead to more effective wound healing,
responses to vaccination and resistance to infection and cancer. Immunopathology resulting from
severe acute stress or persistent stress may promote pro-inflammatory and autoimmune diseases.
Immunosuppression resulting from chronic stress
may reduce the effectiveness of wound healing
and vaccination and increase the risk of infection
and cancer. By contrast, chronic stress may reduce
the risk of pro-inflammatory and autoimmune diseases by suppressing aspects of immune function
that contribute to such conditions (e.g., T lymphocyte activity, cytokine production) [1].
Both acute exercise [164] and chronic training
[165, 166] increase antibody production in
response to vaccination. Mild repeated stress
resulting from chronic training also improves the
rate of wound healing [167], decreases the risk of
upper respiratory illness [168] and reduces the
prevalence and severity of various chronic diseases [169]. Although more work is needed to
define their precise role, it is likely that stress
hormones mediate some of these benefits of
exercise.
Summary
A variety of non-harmful stimuli during exercise
induce the release of stress hormones. These
stress hormones influence many physiological
systems, including the immune system. Stress
hormones act to mobilise immune cells into the
circulation and can increase or decrease the activity of these cells. The precise nature of the inter-
260
action between stress hormones and immune
cells likely depends on multiple factors, including the intensity and duration of exercise, the
physical fitness of exercising individuals and
environmental conditions. Some stress hormones
(e.g., catecholamines) influence immune cell
activity mainly during exercise, whereas others
(e.g., cortisol) may have a more delayed effect on
immune function during the later stages of exercise and/or after exercise. Nutritional interventions such as carbohydrate and caffeine
supplementation can alter the secretion of stress
hormones during exercise, but these alterations
do not always result in changes in immune function. Immunoendocrine interactions during exercise may serve to promote some aspects of health.
However, further research is needed to understand the biological significance of such interactions in more detail.
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